statistics phd placement

Ph.D. in Statistics

Our doctoral program in statistics gives future researchers preparation to teach and lead in academic and industry careers.

Program Description

Degree type.

approximately 5 years

The relatively new Ph.D. in Statistics strives to be an exemplar of graduate training in statistics. Students are exposed to cutting edge statistical methodology through the modern curriculum and have the opportunity to work with multiple faculty members to take a deeper dive into special topics, gain experience in working in interdisciplinary teams and learn research skills through flexible research electives. Graduates of our program are prepared to be leaders in statistics and machine learning in both academia and industry.

The Ph.D. in Statistics is expected to take approximately five years to complete, and students participate as full-time graduate students.  Some students are able to finish the program in four years, but all admitted students are guaranteed five years of financial support.  

Within our program, students learn from global leaders in statistics and data sciences and have:

20 credits of required courses in statistical theory and methods, computation, and applications

18 credits of research electives working with two or more faculty members, elective coursework (optional), and a guided reading course

Dissertation research

Coursework Timeline

Year 1: focus on core learning.

The first year consists of the core courses:

• SDS 384.2 Mathematical Statistics I
• SDS 383C Statistical Modeling I
• SDS 387 Linear Models
• SDS 384.11 Theoretical Statistics
• SDS 383D Statistical Modeling II
• SDS 386D Monte Carlo Methods

In addition to the core courses, students of the first year are expected to participate in SDS 190 Readings in Statistics. This class focuses on learning how to read scientific papers and how to grasp the main ideas, as well as on practicing presentations and getting familiar with important statistics literature.

At the end of the first year, students are expected to take a written preliminary exam. The examination has two purposes: to assess the student’s strengths and weaknesses and to determine whether the student should continue in the Ph.D. program. The exam covers the core material covered in the core courses and it consists of two parts: a 3-hour closed book in-class portion and a take-home applied statistics component. The in-class portion is scheduled at the end of the Spring Semester after final exams (usually late May). The take-home problem is distributed at the end of the in-class exam, with a due-time 24 hours later. 

Year 2: Transitioning from Student to Researcher

In the second year of the program, students take the following courses totaling 9 credit hours each semester:

• Required: SDS 190 Readings in Statistics (1 credit hour)
• Required: SDS 389/489 Research Elective* (3 or 4 credit hours) in which the student engages in independent research under the guidance of a member of the Statistics Graduate Studies Committee
• One or more elective courses selected from approved electives ; and/or
• One or more sections of SDS 289/389/489 Research Elective* (2 to 4 credit hours) in which the student engages in independent research with a member(s) of the Statistics Graduate Studies Committee OR guided readings/self-study in an area of statistics or machine learning. 
• Internship course (0 or 1 credit hour; for international students to obtain Curricular Practical Training; contact Graduate Coordinator for appropriate course options)
• GRS 097 Teaching Assistant Fundamentals or NSC 088L Introduction to Evidence-Based Teaching (0 credit hours; for TA and AI preparation)

* Research electives allow students to explore different advising possibilities by working for a semester with a particular professor. These projects can also serve as the beginning of a dissertation research path. No more than six credit hours of research electives can be taken with a single faculty member in a semester.

Year 3: Advance to Candidacy

Students are encouraged to attend conferences, give presentations, as well as to develop their dissertation research. At the end of the second year or during their third year, students are expected to present their plan of study for the dissertation in an Oral candidacy exam. During this exam, students should demonstrate their research proficiency to their Ph.D. committee members. Students who successfully complete the candidacy exam can apply for admission to candidacy for the Ph.D. once they have completed their required coursework and satisfied departmental requirements. The steps to advance to candidacy are:

• Discuss potential candidacy exam topics with advisor
• Propose Ph.D. committee: the proposed committee must follow the Graduate School and departmental regulations on committee membership for what will become the Ph.D. Dissertation Committee
•   Application for candidacy

Year 4+: Dissertation Completion and Defense

Students are encouraged to attend conferences, give presentations, as well as to develop their dissertation research. Moreover, they are expected to present part of their work in the framework of the department's Ph.D. poster session.

Students who are admitted to candidacy will be expected to complete and defend their Ph.D. thesis before their Ph.D. committee to be awarded the degree. The final examination, which is oral, is administered only after all coursework, research and dissertation requirements have been fulfilled. It is expected that students will be prepared to defend by the end of their fifth year in the doctoral program.

General Information and Expectations for All Ph.D. students

• 2023-24 Student Handbook
• Annual Review At the end of every spring semester, students in their second year and beyond are expected to fill out an annual review form distributed by the Graduate Program Administrator. 
• Seminar Series All students are expected to attend the SDS Seminar Series
• SDS 189R Course Description (when taken for internship)
• Internship Course Registration form
• Intel Corporation
• Berry Consultants

Attending Conferences 

Students are encouraged to attend conferences to share their work. All research-related travel while in student status require prior authorization.

• Request for Travel Authorization (both domestic and international travel)
• Request for Authorization for International Travel  

Graduate Student Handbook (Coming Soon: New Graduate Student Handbook)

Phd program overview.

The PhD program prepares students for research careers in probability and statistics in academia and industry. Students admitted to the PhD program earn the MA and MPhil along the way. The first year of the program is spent on foundational courses in theoretical statistics, applied statistics, and probability. In the following years, students take advanced topics courses. Research toward the dissertation typically begins in the second year. Students also have opportunities to take part in a wide variety of projects involving applied probability or applications of statistics.

Students are expected to register continuously until they distribute and successfully defend their dissertation. Our core required and elective curricula in Statistics, Probability, and Machine Learning aim to provide our doctoral students with advanced learning that is both broad and focused. We expect our students to make Satisfactory Academic Progress in their advanced learning and research training by meeting the following program milestones through courseworks, independent research, and dissertation research:

By the end of year 1: passing the qualifying exams;

By the end of year 2: fulfilling all course requirements for the MA degree and finding a dissertation advisor;

By the end of year 3: passing the oral exam (dissertation prospectus) and fulfilling all requirements for the MPhil degree

By the end of year 5: distributing and defending the dissertation.

We believe in the Professional Development value of active participation in intellectual exchange and pedagogical practices for future statistical faculty and researchers. Students are required to serve as teaching assistants and present research during their training. In addition, each student is expected to attend seminars regularly and participate in Statistical Practicum activities before graduation.

We provide in the following sections a comprehensive collection of the PhD program requirements and milestones. Also included are policies that outline how these requirements will be enforced with ample flexibility. Questions on these requirements should be directed to ADAA Cindy Meekins at [email protected] and the DGS, Professor John Cunningham at [email protected] .

Applications for Admission

• Our students receive very solid training in all aspects of modern statistics. See Graduate Student Handbook for more information.
• Our students receive Fellowship and full financial support for the entire duration of their PhD. See more details here .
• Our students receive job offers from top academic and non-academic institutions .
• Our students can work with world-class faculty members from Statistics Department or the Data Science Institute .
• Our students have access to high-speed computer clusters for their ambitious, computationally demanding research.
• Our students benefit from a wide range of seminars, workshops, and Boot Camps organized by our department and the data science institute .
• Suggested Prerequisites: A student admitted to the PhD program normally has a background in linear algebra and real analysis, and has taken a few courses in statistics, probability, and programming. Students who are quantitatively trained or have substantial background/experience in other scientific disciplines are also encouraged to apply for admission.
• GRE requirement: Waived for Fall 2024.
• Language requirement: The English Proficiency Test requirement (TOEFL) is a Provost's requirement that cannot be waived.
• The Columbia GSAS minimum requirements for TOEFL and IELTS are: 100 (IBT), 600 (PBT) TOEFL, or 7.5 IELTS. To see if this requirement can be waived for you, please check the frequently asked questions below.
• Deadline: Jan 8, 2024 .
• Application process: Please apply by completing the Application for Admission to the Columbia University Graduate School of Arts & Sciences .
• Timeline: P.hD students begin the program in September only.  Admissions decisions are made in mid-March of each year for the Fall semester.

Frequently Asked Questions

• What is the application deadline? What is the deadline for financial aid? Our application deadline is January 5, 2024 .
• Can I meet with you in person or talk to you on the phone? Unfortunately given the high number of applications we receive, we are unable to meet or speak with our applicants.
• What are the required application materials? Specific admission requirements for our programs can be found here .
• Due to financial hardship, I cannot pay the application fee, can I still apply to your program? Yes. Many of our prospective students are eligible for fee waivers. The Graduate School of Arts and Sciences offers a variety of application fee waivers . If you have further questions regarding the waiver please contact  gsas-admissions@ columbia.edu .
• How many students do you admit each year? It varies year to year. We finalize our numbers between December - early February.
• What is the distribution of students currently enrolled in your program? (their background, GPA, standard tests, etc)? Unfortunately, we are unable to share this information.
• How many accepted students receive financial aid? All students in the PhD program receive, for up to five years, a funding package consisting of tuition, fees, and a stipend. These fellowships are awarded in recognition of academic achievement and in expectation of scholarly success; they are contingent upon the student remaining in good academic standing. Summer support, while not guaranteed, is generally provided. Teaching and research experience are considered important aspects of the training of graduate students. Thus, graduate fellowships include some teaching and research apprenticeship. PhD students are given funds to purchase a laptop PC, and additional computing resources are supplied for research projects as necessary. The Department also subsidizes travel expenses for up to two scientific meetings and/or conferences per year for those students selected to present. Additional matching funds from the Graduate School Arts and Sciences are available to students who have passed the oral qualifying exam.
• Can I contact the department with specific scores and get feedback on my competitiveness for the program? We receive more than 450 applications a year and there are many students in our applicant pool who are qualified for our program. However, we can only admit a few top students. Before seeing the entire applicant pool, we cannot comment on admission probabilities.
• What is the minimum GPA for admissions? While we don’t have a GPA threshold, we will carefully review applicants’ transcripts and grades obtained in individual courses.
• Is there a minimum GRE requirement? No. The general GRE exam is waived for the Fall 2024 admissions cycle. 
• Can I upload a copy of my GRE score to the application? Yes, but make sure you arrange for ETS to send the official score to the Graduate School of Arts and Sciences.
• Is the GRE math subject exam required? No, we do not require the GRE math subject exam.
• What is the minimum TOEFL or IELTS  requirement? The Columbia Graduate School of Arts and Sciences minimum requirements for TOEFL and IELTS are: 100 (IBT), 600 (PBT) TOEFL, or 7.5 IELTS
•  I took the TOEFL and IELTS more than two years ago; is my score valid? Scores more than two years old are not accepted. Applicants are strongly urged to make arrangements to take these examinations early in the fall and before completing their application.
• I am an international student and earned a master’s degree from a US university. Can I obtain a TOEFL or IELTS waiver? You may only request a waiver of the English proficiency requirement from the Graduate School of Arts and Sciences by submitting the English Proficiency Waiver Request form and if you meet any of the criteria described here . If you have further questions regarding the waiver please contact  gsas-admissions@ columbia.edu .
• My transcript is not in English. What should I do? You have to submit a notarized translated copy along with the original transcript.

Can I apply to more than one PhD program? You may not submit more than one PhD application to the Graduate School of Arts and Sciences. However, you may elect to have your application reviewed by a second program or department within the Graduate School of Arts and Sciences if you are not offered admission by your first-choice program. Please see the application instructions for a more detailed explanation of this policy and the various restrictions that apply to a second choice. You may apply concurrently to a program housed at the Graduate School of Arts and Sciences and to programs housed at other divisions of the University. However, since the Graduate School of Arts and Sciences does not share application materials with other divisions, you must complete the application requirements for each school.

How do I apply to a dual- or joint-degree program? The Graduate School of Arts and Sciences refers to these programs as dual-degree programs. Applicants must complete the application requirements for both schools. Application materials are not shared between schools. Students can only apply to an established dual-degree program and may not create their own.

With the sole exception of approved dual-degree programs , students may not pursue a degree in more than one Columbia program concurrently, and may not be registered in more than one degree program at any institution in the same semester. Enrollment in another degree program at Columbia or elsewhere while enrolled in a Graduate School of Arts and Sciences master's or doctoral program is strictly prohibited by the Graduate School. Violation of this policy will lead to the rescission of an offer of admission, or termination for a current student.

When will I receive a decision on my application? Notification of decisions for all PhD applicants generally takes place by the end of March.

Notification of MA decisions varies by department and application deadlines. Some MA decisions are sent out in early spring; others may be released as late as mid-August.

Can I apply to both MA Statistics and PhD statistics simultaneously?  For any given entry term, applicants may elect to apply to up to two programs—either one PhD program and one MA program, or two MA programs—by submitting a single (combined) application to the Graduate School of Arts and Sciences.  Applicants who attempt to submit more than one Graduate School of Arts and Sciences application for the same entry term will be required to withdraw one of the applications.

The Graduate School of Arts and Sciences permits applicants to be reviewed by a second program if they do not receive an offer of admission from their first-choice program, with the following restrictions:

• This option is only available for fall-term applicants.
• Applicants will be able to view and opt for a second choice (if applicable) after selecting their first choice. Applicants should not submit a second application. (Note: Selecting a second choice will not affect the consideration of your application by your first choice.)
• Applicants must upload a separate Statement of Purpose and submit any additional supporting materials required by the second program. Transcripts, letters, and test scores should only be submitted once.
• An application will be forwarded to the second-choice program only after the first-choice program has completed its review and rendered its decision. An application file will not be reviewed concurrently by both programs.
• Programs may stop considering second-choice applications at any time during the season; Graduate School of Arts and Sciences cannot guarantee that your application will receive a second review.
• What is the mailing address for your PhD admission office? Students are encouraged to apply online . Please note: Materials should not be mailed to the Graduate School of Arts and Sciences unless specifically requested by the Office of Admissions. Unofficial transcripts and other supplemental application materials should be uploaded through the online application system. Graduate School of Arts and Sciences Office of Admissions Columbia University  107 Low Library, MC 4303 535 West 116th Street  New York, NY 10027
• How many years does it take to pursue a PhD degree in your program? Our students usually graduate in 4‐6 years.
• Can the PhD be pursued part-time? No, all of our students are full-time students. We do not offer a part-time option.
• One of the requirements is to have knowledge of linear algebra (through the level of MATH V2020 at Columbia) and advanced calculus (through the level of MATH V1201). I studied these topics; how do I know if I meet the knowledge content requirement? We interview our top candidates and based on the information on your transcripts and your grades, if we are not sure about what you covered in your courses we will ask you during the interview.
• Can I contact faculty members to learn more about their research and hopefully gain their support? Yes, you are more than welcome to contact faculty members and discuss your research interests with them. However, please note that all the applications are processed by a central admission committee, and individual faculty members cannot and will not guarantee admission to our program.
• How do I find out which professors are taking on new students to mentor this year?  Applications are evaluated through a central admissions committee. Openings in individual faculty groups are not considered during the admissions process. Therefore, we suggest contacting the faculty members you would like to work with and asking if they are planning to take on new students.

For more information please contact us at [email protected] .

For more information please contact us at  [email protected]

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Cornell University does not offer a separate Masters of Science (MS) degree program in the field of Statistics. Applicants interested in obtaining a masters-level degree in statistics should consider applying to Cornell's MPS Program in Applied Statistics.

Choosing a Field of Study

There are many graduate fields of study at Cornell University. The best choice of graduate field in which to pursue a degree depends on your major interests. Statistics is a subject that lies at the interface of theory, applications, and computing. Statisticians must therefore possess a broad spectrum of skills, including expertise in statistical theory, study design, data analysis, probability, computing, and mathematics. Statisticians must also be expert communicators, with the ability to formulate complex research questions in appropriate statistical terms, explain statistical concepts and methods to their collaborators, and assist them in properly communicating their results. If the study of statistics is your major interest then you should seriously consider applying to the Field of Statistics.

There are also several related fields that may fit even better with your interests and career goals. For example, if you are mainly interested in mathematics and computation as they relate to modeling genetics and other biological processes (e.g, protein structure and function, computational neuroscience, biomechanics, population genetics, high throughput genetic scanning), you might consider the Field of Computational Biology . You may wish to consider applying to the Field of Electrical and Computer Engineering if you are interested in the applications of probability and statistics to signal processing, data compression, information theory, and image processing. Those with a background in the social sciences might wish to consider the Field of Industrial and Labor Relations with a major or minor in the subject of Economic and Social Statistics. Strong interest and training in mathematics or probability might lead you to choose the Field of Mathematics . Lastly, if you have a strong mathematics background and an interest in general problem-solving techniques (e.g., optimization and simulation) or applied stochastic processes (e.g., mathematical finance, queuing theory, traffic theory, and inventory theory) you should consider the Field of Operations Research .

Residency Requirements

Students admitted to PhD program must be "in residence" for at least four semesters, although it is generally expected that a PhD will require between 8 and 10 semesters to complete. The chair of your Special Committee awards one residence unit after the satisfactory completion of each semester of full-time study. Fractional units may be awarded for unsatisfactory progress.

Your Advisor and Special Committee

The Director of Graduate Studies is in charge of general issues pertaining to graduate students in the field of Statistics. Upon arrival, a temporary Special Committee is also declared for you, consisting of the Director of Graduate Studies (chair) and two other faculty members in the field of Statistics. This temporary committee shall remain in place until you form your own Special Committee for the purposes of writing your doctoral dissertation. The chair of your Special Committee serves as your primary academic advisor; however, you should always feel free to contact and/or chat with any of the graduate faculty in the field of Statistics.

The formation of a Special Committee for your dissertation research should serve your objective of writing the best possible dissertation. The Graduate School requires that this committee contain at least three members that simultaneously represent a certain combination of subjects and concentrations. The chair of the committee is your principal dissertation advisor and always represents a specified concentration within the subject & field of Statistics. The Graduate School additionally requires PhD students to have at least two minor subjects represented on your special committee. For students in the field of Statistics, these remaining two members must either represent (i) a second concentration within the subject of Statistics, and one external minor subject; or, (ii) two external minor subjects. Each minor advisor must agree to serve on your special committee; as a result, the identification of these minor members should occur at least 6 months prior to your A examination.

Some examples of external minors include Computational Biology, Demography, Computer Science, Economics, Epidemiology, Mathematics, Applied Mathematics and Operations Research. The declaration of an external minor entails selecting (i) a field other than Statistics in which to minor; (ii) a subject & concentration within the specified field; and, (iii) a minor advisor representing this field/subject/concentration that will work with you in setting the minor requirements. Typically, external minors involve gaining knowledge in 3-5 graduate courses in the specified field/subject, though expectations can vary by field and even by the choice of advisor. While any choice of external minor subject is technically acceptable, the requirement that the minor representative serve on your Special Committee strongly suggests that the ideal choice(s) should share some natural connection with your choice of dissertation topic.

The fields, subjects and concentrations represented on your committee must be officially recognized by the Graduate School ; the Degrees, Subjects & Concentrations tab listed under each field of study provides this information. Information on the concentrations available for committee members chosen to represent the subject of Statistics can be found on the Graduate School webpage . 

Statistics PhD Travel Support

The Department of Statistics and Data Science has established a fund for professional travel for graduate students. The intent of the Department is to encourage travel that enhances the Statistics community at Cornell by providing funding for graduate students in statistics that will be presenting at conferences. Please review the Graduate Student Travel Award Policy website for more information. 

Completion of the PhD Degree

In addition to the specified residency requirements, students must meet all program requirements as outlined in Program Course Requirements and Timetables and Evaluations and Examinations, as well as complete a doctoral dissertation approved by your Special Committee. The target time to PhD completion is between 4 and 5 years; the actual time to completion varies by student.

Students should consult both the Guide to Graduate Study and Code of Legislation of the Graduate Faculty (available at www.gradschool.cornell.edu ) for further information on all academic and procedural matters pertinent to pursuing a graduate degree at Cornell University.

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College of Liberal Arts and Sciences

Department of Statistics

Ph.d. placements.

After they graduate, alumni of the statistics Ph.D. program go on to work at colleges and universities in research, teaching, and tenure-track positions. They also take on a wide variety of roles in public and private organizations.

Recent Graduates

Learn more about the first jobs our Ph.D. alumni land after earning their degrees.

Class of 2023

Prince Allotey , Asst. Professor of Practice, University of Washington Anhar Aloufi Eric Baron , Senior Biostatistician, Servier Pharmaceuticals Xiaolin Chang , Biostatistician, Moderna Jianmin Chen Simiao Gao , Postdoctoral Research Fellow, Yale University Zijian Huang , Quantitative Analytics Specialist, Wells Fargo Yakov Khariton Jackson Lautier , Asst. Professor,  Bentley University Jung Wun Lee , Postdoctoral Research Fellow, Harvard T.H. Chan School of Public Health Jing Li Yifan Li , Senior Consultant, Ernst & Young Daeyoung Lim , Mathematical Statistician, CDER, FDA Peiran Liu , Mathematical Statistician, CBER, FDA Zhongmao Liu , Mathematical Statistician, CDER, FDA Austin Menger , Founder, Menger Analytics Namitha Pais , Postdoctoral Research, U.S. Dept. of Agriculture Jiwon Park , Postdoctoral Fellow, Johns Hopkins University, Dept. of Epidemiology Yong Qiao , Sr. Assoc. Data Scientist, Travelers Jingyu Sun , Statistical Data Scientist , Revolution Medicines Boyang Tang , Mathematical Statistician, FDA Patrick Toman , Data Scientist, Hartford Steam Boiler Ziyang Wang , Wells Fargo Ganchao Wei Hao Wu , Mathematical Statistician, CBER, FDA Meiruo Xiang , Mathematical Statistician, CDER, FDA Zehan Yang Yelie Yuan , CCB Risk Program Associate, JP Morgan Chase Katherine Zavez , Postdoctoral Research, UConn Haiwei Zhou , Senior Statistician, AbbVie

More Ph.D. Placements

Yuen Tsz (Abby) Lau , Postdoctoral Associate, University of Pennsylvania, Biostatistics

Sai Ma , Senior Biostatistician, Vertex Pharmaceuticals

Lubing Wang , Senior Associate, Travelers

Zhiyong Hu , Data Scientist, Microsoft

Srawan Bishnoi , Teaching Asst. Professor, University of Pittsburgh

Cheng Huang , Statistician, Vir Biotechnology

Wenlin Yuan , Statistician, Moderna

Hongfei Li , Principle Biostatistician, Incyte Corporation

Yiming Zhang , Mathematical Statistician, FDA

Md. Tuhin Sheikh , Postdoctoral Associate, Yale University

Chiranjit Dutta, Applied Researcher, Ebay

Wei Shi , Senior Statistician, Modeling & Simulation, Amgen

Yaqiong Yao , Postdoctoral Research Scientist, Columbia University, Biostatistics

Wanwan Xu , Postdoctoral Associate, Yale University

Xiaomeng Li, Senior Consultant, Ernst & Young

Biju Wang , Senior Biostatistician, Johnson & Johnson

Yan Li , Postdoctoral Fellow, University of Michigan, Biostatistics

Soumik Banerjee , Visiting Asst. Professor, Binghamton University

Jiyeon Song , Postdoctoral Fellow, University of Michigan, Biostatistics

Zhe Sun , Post Doc, Yale University

JooChul Lee , University of Pennsylvania, Dept. of Biostatistics and Epidemiology

Ziqi Yang , Ant Group

Qingyang Liu , Incyte Corporation

Jinjian Mu , Ohio State University, College of Nursing

Shuang Yin , Transamerica Insurance

Ellis Shaffer , S & P Global

Cheng Zhang , Novartis

Qi Qi , Genetech

Zhe Wang , Asst. Prof., Denison University

Aritra Halder , Asst. Prof., University of Virginia, Bio-Complexity Institute

Lijiang Geng , Boehringer Ingelheim, Shanghai

Yulia Sidi , Takeda

Xiaokang Liu , University of Pennsylvania, Postdoc

Jieying Jiao , Travelers Insurance

Chaoran Hu , Eli Lilly and Company

Renjie Chen , Zillow

Kangyang Liu , CTO Office, Motorola Solutions Company

Yishu Xue , Travelers Insurance

Yang Liu , Upstart

Tairan Ye , Liberty Mutual Insurance

Matthew Henry Linder , Oden Technologies

Qian Meng , Trinity

Disheng Mao , Microsoft

Wenjie Wang , Eli Lilly and Company

Paul McLaughlin , Penn State University

Di Zheng , Liberty Mutual Insurance

Yeongjin Gwon , University of Nebraska Medical Center

Jun Hu , University of Vermont

Hao Li , Boehringer Ingelheim

Shariq Mohammed , University of Michigan

Ruochen Zha , Mapfre Insurance

Fan Zhang , Pfizer

Chen Zhang , Travelers Insurance

Yan Zhuang , Connecticut College

Yaohua Zhang , Vertex Pharmaceuticals

Ved Deshpande , Ebay

Aditya Mishra , Flatiron Institute

Abhishek Bishoyi , Selective Insurance

Sudeep Bapat , University of California, Santa Barbara

Jing Wu , University of Rhode Island

Daoyuan Shi , Vertex Pharmaceuticals

Chongliang Luo , UConn Health Center

Yujing Jiang , Colorado State University

Gregory Vaughan , Bentley University

Dooti Roy , Boehringer Ingelheim

Wei Fu , Mapfre Insurance

Brian Bader , KPMG

Abhisek Saha , MD Anderson Cancer Institute

Qianzhu Wu , Liberty Mutual Insurance Co.

Yu-Bo Wang , National Institute of Child Health & Human Development (NICHD/NIH)

Chun Wang , Liberty Mutual Insurance Co.

Hee-Koung Joeng , Merck

Patrick Harrington , Genomic Health, Inc.

Bo Zhao , Travelers Insurance

Dooti Roy , Biostatistician, Boehringer Ingelheim

Zhuo Wang , Shenzen University

Volodymyr Serhiyenko , Metabiota

Guang Ouyang , Data Scientist, Id Analytics

Chantal Larose , Assistant Professor, SUNY New Paltz

Gyuhyeong Goh , Assistant Professor, Kansas State University

Danjie Zhang , Biostatistician, Gilead Sciences, Inc.

Swarnali Banerjee , Assistant Professor, Old Dominion College

Sankha Perrera , Linear Squared

Hongwei Shang , Hewlett Packard

Ashok Chaurasia , Postdoctoral Fellow, National Institute of Child Health & Human Dev.

Gong-Yi Liao , Northern Trust

Hongwei Shang , Researcher, Hewlett Packard Labs

Jennifer Boyko , Biostatistician, Boehringer Ingelheim

Sairam Rayaprolu , Decision Science Consultant, Disney

Steven Chiou , Assistant Professor, University of Minnesota, Duluth

Valerie Pare , Wesleyan University

Xiao (Leo) Wang , Assistant Vice President, Barclay’s

Xun Jiang , Statistician, Amgen

Bhargab Chattopadhyay , Assistant Professor, University of Texas at Dallas

Hui Yao , Ernst & Young

Karthik Bharath , Visiting Assistant Professor at Department of Statistics, Ohio State University

Ran Liu , Biometrician, Merck

Rui Wu , Statistician, Novartis

Wenqing Li , Novartis

Yuanye Zhang , Senior Biostatistician, Novartis

Ziwen Wei , Statistician, Merck

Arijit Sinha , Novartis

Debanjan Bhattacharjee , Assistant Professor, Department of Mathematics, Utah Valley University

Gregory Matthews , Postdoctoral Research Associate, School of Public Health, University of Massachusetts

Jeffrey Stratton , Postdoctoral Research Associate, Department of Mathematics, University of Massachusetts, Amherst, MA.

Marcos Prates , Federal University of Minas Gerais

Miaomiao Ge , Statistician, Boehringer Ingelheim

Xiaojing Wang , Google, New York City

Sandra Hurtado-Rua , Postdoctoral Associate Division of Biostatistics and Epidemiology Department of Public Health Weill Medical College of Cornell University

Yuchen Fama , Statistician, Travelers, Hartford, CT.

Balaji Raman , Visiting Assistant Professor, Department of Statistics, Yale University, CT

Elijah Gaioni , IBM, TJ Watson, NY

Jian Zou , Postdoctoral Fellow, NISS, North Carolina

Patrick Joyce , Census Bureau

Wangang Xie , Statistician, Abbott Laboratories, Illinois

Xia Wang , Postdoctoral Fellow, NISS, North Carolina

Yifang Zhao

Sourish Das , Postdoctoral Fellow/Visiting Faculty, SAMSI/Duke University, Durham, NC

Yingmei Xi , Averion International Corp., Southborough, MA

Fang Yu , Biostatistics, University of Nebraska, Omaha

Feng Guo , Department of Statistics, Virginia Tech University, Blacksburg, VA

Jaydip Mukhopadhyay , Bristol Myers Squibb, Wallingford, CT

William Pepe , AT&T, NJ

Changhong Song , Biostatistician at EMMES Corporation in Rockville, Maryland.

Samiran Ghosh , Mathematical Sciences Dept, Indiana University Purdue University at Indianapolis

Sonali Das , Council for Scientific and Industrial Research, Pretoria, South Africa

Ulysses Diva , Bristol Meyers & Squibb, Wallingford, CT

Hai Xu , Statistician, St. Paul Travelers, Hartford, CT.

Seongho Song , Department of Mathematics, University of Cincinnati, Ohio.

Zhaohui Liu , Senior Biostatistician, Novartis, Inc., NJ.

Zhenkui Zhang , Statistical Analyst, Liberty Mutual Bank, Boston, MA.

Anandamayee Majumdar , Department of Mathematics, Arizona State University, Arizona

Lan Huang , National Cancer Institute, National Institute of Health, Rockville, Maryland.

Madhuja Mallick , Biostatistician, Merck Research Laboratories.

Prashni Paliwal , Biostatistician, Bristol-Myers Squibb, Wallingford, CT

Shanshan Wu , Statistician, ING Clarion, New York, NY

Amitabha Bhaumik , Bristol-Myers-Squibb

Junfeng Liu , Department of Statistics, Case Western Reserve University, Cleveland

Rongwei Fu , School of Public Health, Oregon Science and Health University, Portland, Oregon

Greg Cicconetti

Jun Ying , Professor, Department of Environmental Health, Division of Biostatistics and Bioinformatics, University of Cincinnati

Athanasios Micheas , Department of Statistics, University of Missouri, Columbia, MO

Deepak K. Agarwal , Yahoo Corporation

Zhen Chen , Biostatistics, University of Pennsylvania

Athanasios Kottas , University of California, Santa Cruz, CA

Fei Wang , Assistant Professor,Public Health School, Boston University

Kaushik Patra , Center for Biostatistics and AIDS Research, Harvard University, Cambridge, MA

Keith Holler , St. Pauls Travelers Insurance, Hartford, CT

Sudipto Banerjee , Biostatistics Dept, University of Minnesota

Kenneth Klesczewski , Research Statistician, Bristol Myers Squibb , Wallingford, CT

William Duggan , Research Statistician, Pfizer, Groton, CT

Hui-May Chu , Statistician/Computing Scientist, CPBD, Inc. Cambridge, MA

Jie Chen , Statistician, Computing Service Dept. UMASS, Boston, MA

Murali Niverthi , Lincoln National Corp, Fort Wayne, IN

Malini Iyengar , Glaxo Smith Klein, Philadelphia, PA Mark Ecker , University of Northern Iowa, Cedar Falls, IA Zuqiang Qiou , Vital Computer Services International Inc., Florham Park, NJ

Dan Larose , Central Connecticut State University, New Britain, CT

Kuo-ren Lou , Tamkang University, Taiwan, ROC

Marco Bonetti , Institute of Quantitative Methods, Universita Bocconi, Milano, Italy

Pantelis Vlachos , Carnegie Mellon University, Pittsburgh, PA

Sujit Ghosh , North Carolina State University, Raleigh, NC

Cristina Sison , North Shore University Hospital, NY

Hong Chang , Cooper and Lybrand, Boston, MA

Jeffrey Pai , University of Manitoba, Canada

Sujay Datta , Texas A&M University, College Station, TX

Tae Yang , Myongji University, Korea

Bani Mallick , Texas A&M University, College Station, TX

Fengchun Peng , Department of Biostatistics, University of Rochester

Lea R. Birmiwal , Birminal Investment Trust

Sujit Sahu , School of Mathematics, University of Southampton, U.K.

Saibal Chattopadhyay , Indian Institute of Management, Calcutta, India

Tai-Ming Lee , Department of Statistics, Fu Jen Catholic University, Taiwan

Constantine Yiannoutsos , Department of Biostatistics, Indiana University-Purdue University

Tumulesh Solanky , Professor,Department of Mathematics, University of New Orleans

Younshik Chung , Professor, Pusan National University, Korea

Brad Carlin , School of Public Health, Division of Biostatistics, University of Minnesota

Daniel Miller , Central Connecticut State University

Mabel H. Moreno

Pei-San Liao , Fu Jen Catholic University, Taiwan

Phyllis Schumacher , Mathematics Department, Bryant College

John Judge , Westfield State College

James Kenyon , Senior Research Biostatistician, Bristol-Myers Squibb

Patrick Cantwell , Business Div, Bureau of the Census

Silvi Liberman , Statistics Department, Temple University (Deceased)

Steve Leeds , President, The Marketing Investigators

Suryoguritno Darmanto , Godjah Mada University, Indonesia

Marsha Davis , Math and Computer Sciences Dept, Eastern Connecticut State University

Robert Leighty , Department of Statistics, Ohio State University

John F. Carter , Donnelley Marketing Information Services

William R. Stephenson , Department of Statistics, Iowa State University

Eleanor J. Dietz , Mathematics Dept., Meredith College, Raleigh, WC

Brian W. Woodruff

Lawrence C. Berger

Michael A. Fligner , Statistics Dept., Ohio State University

Michael J. Barthel , DC Dept. of Human Services

Labib J. Abdunnur

Richard C. Murphy

Teng-Shan Weng

William A. Powers III

David F. Bauer , Math Science, Virginia Commonwealth University

Oswald G. DeLisser

Richard H. Lavoie , Dept. of Mathematics, Providence College

Bodh R. Gulati , Southern Connecticut State University

David L. Fulton

Matthew Goldstein , Chancellor, CUNY

Mrs. Gene S. Sogliero

Shadeo K. Badhe

Chris P. Tsokos , Dept. of Mathematics, University of South Florida

Donald Fridshal

Jimmie Dale Woods

Leigh Harrington

David Salsburg , Statistical Consultant (our very first Ph.D.)

Vidya S. Taneja , Dept. of Mathematics, Western Illinois University

Class of 2022

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Department of Statistics

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• Open Positions
• PhD Program

The department encourages research in both theoretical and applied statistics. Faculty members of the department have been leaders in research on a multitude of topics that include statistical inference, statistical computing and Monte-Carlo methods, analysis of missing data, causal inference, stochastic processes, multilevel models, experimental design, network models and the interface of statistics and the social, physical, and biological sciences. A unique feature of the department lies in the fact that apart from methodological research, all the faculty members are also heavily involved in applied research, developing novel methodology that can be applied to a wide array of fields like astrophysics, biology, chemistry, economics, engineering, public policy, sociology, education and many others.

Two carefully designed special courses offered to Ph.D. students form a unique feature of our program. Among these, Stat 303 equips students with the  basic skills necessary to teach statistics , as well as to be better overall statistics communicators. Stat 399 equips them with generic skills necessary for problem solving abilities.

Our Ph.D. students often receive substantial guidance from several faculty members, not just from their primary advisors, and in several settings. For example, every Ph.D. candidate who passes the qualifying exam gives a 30 minute presentation each semester (in Stat 300 ), in which the faculty ask questions and make comments. The Department recently introduced an award for Best Post-Qualifying Talk (up to two per semester), to further encourage and reward inspired research and presentations.

PhD Program Requirements

PhD Program Admissions Process

• PhD Admissions FAQ
• AM in Statistics
• Stat 300: Research in Statistics
• Stat 303: The Art and Practice of Teaching Statistics

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Department of Statistics and Data Science

Ph.d. program.

Fields of study include the main areas of statistical theory (with emphasis on foundations, Bayes theory, decision theory, nonparametric statistics), probability theory (stochastic processes, asymptotics, weak convergence), information theory, bioinformatics and genetics, classification, data mining and machine learning, neural nets, network science, optimization, statistical computing, and graphical models and methods.

With this background, graduates of the program have found excellent positions in universities, industry, and government. See the list of alumni for examples.

PhD Program

Advanced undergraduate or masters level work in mathematics and statistics will provide a good background for the doctoral program. Quantitatively oriented students with degrees in other scientific fields are also encouraged to apply for admission. In particular, the department has expanded its research and educational activities towards computational biology, mathematical finance and information science. The doctoral program normally takes four to five years to complete.

Doctoral Program in Statistics

Statistics phd minor.

PhD Program information

The Statistics PhD program is rigorous, yet welcoming to students with interdisciplinary interests and different levels of preparation. Students in the PhD program take core courses on the theory and application of probability and statistics during their first year. The second year typically includes additional course work and a transition to research leading to a dissertation. PhD thesis topics are diverse and varied, reflecting the scope of faculty research interests. Many students are involved in interdisciplinary research. Students may also have the option to pursue a designated emphasis (DE) which is an interdisciplinary specialization:  Designated Emphasis in Computational and Genomic Biology ,  Designated Emphasis in Computational Precision Health ,  Designated Emphasis in Computational and Data Science and Engineering . The program requires four semesters of residence.

Normal progress entails:

Year 1 . Perform satisfactorily in preliminary coursework. In the summer, students are required to embark on a short-term research project, internship, graduate student instructorship, reading course, or on another research activity. Years 2-3 . Continue coursework. Find a thesis advisor and an area for the oral qualifying exam. Formally choose a chair for qualifying exam committee, who will also serve as faculty mentor separate from the thesis advisor.  Pass the oral qualifying exam and advance to candidacy by the end of Year 3. Present research at BSTARS each year. Years 4-5 . Finish the thesis and give a lecture based on it in a department seminar.

Program Requirements

• Qualifying Exam

Course work and evaluation

Preliminary stage: the first year.

Effective Fall 2019, students are expected to take four semester-long courses for a letter grade during their first year which should be selected from the core first-year PhD courses offered in the department: Probability (204/205A, 205B,), Theoretical Statistics (210A, 210B), and Applied Statistics (215A, 215B). These requirements can be altered by a member of the PhD Program Committee (in consultation with the faculty mentor and by submitting a graduate student petition ) in the following cases:

• Students primarily focused on probability will be allowed to substitute one semester of the four required semester-long courses with an appropriate course from outside the department.
• Students may request to postpone one semester of the core PhD courses and complete it in the second year, in which case they must take a relevant graduate course in their first year in its place. In all cases, students must complete the first year requirements in their second year as well as maintain the overall expectations of second year coursework, described below. Some examples in which such a request might be approved are described in the course guidance below.
• Students arriving with advanced standing, having completed equivalent coursework at another institution prior to joining the program, may be allowed to take other relevant graduate courses at UC Berkeley to satisfy some or all of the first year requirements

Requirements on course work beyond the first year

Students entering the program before 2022 are required to take five additional graduate courses beyond the four required in the first year, resulting in a total of nine graduate courses required for completion of their PhD. In their second year, students are required to take three graduate courses, at least two of them from the department offerings, and in their third year, they are required to take at least two graduate courses. Students are allowed to change the timing of these five courses with approval of their faculty mentor. Of the nine required graduate courses, students are required to take for credit a total of 24 semester hours of courses offered by the Statistics department numbered 204-272 inclusive. The Head Graduate Advisor (in consultation with the faculty mentor and after submission of a graduate student petition) may consent to substitute courses at a comparable level in other disciplines for some of these departmental graduate courses. In addition, the HGA may waive part of this unit requirement.

Starting with the cohort entering in the 2022-23 academic year , students are required to take at least three additional graduate courses beyond the four required in the first year, resulting in a total of seven graduate courses required for completion of their PhD. Of the seven required graduate courses, five of these courses must be from courses offered by the Statistics department and numbered 204-272, inclusive. With these reduced requirements, there is an expectation of very few waivers from the HGA. We emphasize that these are minimum requirements, and we expect that students will take additional classes of interest, for example on a S/U basis, to further their breadth of knowledge. 

For courses to count toward the coursework requirements students must receive at least a B+ in the course (courses taken S/U do not count, except for STAT 272 which is only offered S/U).  Courses that are research credits, directed study, reading groups, or departmental seminars do not satisfy coursework requirements (for courses offered by the Statistics department the course should be numbered 204-272 to satisfy the requirements). Upper-division undergraduate courses in other departments can be counted toward course requirements with the permission of the Head Graduate Advisor. This will normally only be approved if the courses provide necessary breadth in an application area relevant to the student’s thesis research.

First year course work: For the purposes of satisfactory progression in the first year, grades in the core PhD courses are evaluated as: A+: Excellent performance in PhD program A: Good performance in PhD program A-: Satisfactory performance B+: Performance marginal, needs improvement B: Unsatisfactory performance First year and beyond: At the end of each year, students must meet with his or her faculty mentor to review their progress and assess whether the student is meeting expected milestones. The result of this meeting should be the completion of the student’s annual review form, signed by the mentor ( available here ). If the student has a thesis advisor, the thesis advisor must also sign the annual review form.

Guidance on choosing course work

Choice of courses in the first year: Students enrolling in the fall of 2019 or later are required to take four semesters of the core PhD courses, at least three of which must be taken in their first year. Students have two options for how to schedule their four core courses:

• Option 1 -- Complete Four Core Courses in 1st year: In this option, students would take four core courses in the first year, usually finishing the complete sequence of two of the three sequences.  Students following this option who are primarily interested in statistics would normally take the 210A,B sequence (Theoretical Statistics) and then one of the 205A,B sequence (Probability) or the 215A,B sequence (Applied Statistics), based on their interests, though students are allowed to mix and match, where feasible. Students who opt for taking the full 210AB sequence in the first year should be aware that 210B requires some graduate-level probability concepts that are normally introduced in 205A (or 204).
• Option 2 -- Postponement of one semester of a core course to the second year: In this option, students would take three of the core courses in the first year plus another graduate course, and take the remaining core course in their second year. An example would be a student who wanted to take courses in each of the three sequences. Such a student could take the full year of one sequence and the first semester of another sequence in the first year, and the first semester of the last sequence in the second year (e.g. 210A, 215AB in the first year, and then 204 or 205A in the second year). This would also be a good option for students who would prefer to take 210A and 215A in their first semester but are concerned about their preparation for 210B in the spring semester.  Similarly, a student with strong interests in another discipline, might postpone one of the spring core PhD courses to the second year in order to take a course in that discipline in the first year.  Students who are less mathematically prepared might also be allowed to take the upper division (under-graduate) courses Math 104 and/or 105 in their first year in preparation for 205A and/or 210B in their second year. Students who wish to take this option should consult with their faculty mentor, and then must submit a graduate student petition to the PhD Committee to request permission for  postponement. Such postponement requests will be generally approved for only one course. At all times, students must take four approved graduate courses for a letter grade in their first year.

After the first year: Students with interests primarily in statistics are expected to take at least one semester of each of the core PhD sequences during their studies. Therefore at least one semester (if not both semesters) of the remaining core sequence would normally be completed during the second year. The remaining curriculum for the second and third years would be filled out with further graduate courses in Statistics and with courses from other departments. Students are expected to acquire some experience and proficiency in computing. Students are also expected to attend at least one departmental seminar per week. The precise program of study will be decided in consultation with the student’s faculty mentor.

Remark. Stat 204 is a graduate level probability course that is an alternative to 205AB series that covers probability concepts most commonly found in the applications of probability. It is not taught all years, but does fulfill the requirements of the first year core PhD courses. Students taking Stat 204, who wish to continue in Stat 205B, can do so (after obtaining the approval of the 205B instructor), by taking an intensive one month reading course over winter break.

Designated Emphasis: Students with a Designated Emphasis in Computational and Genomic Biology or Designated Emphasis in Computational and Data Science and Engineering should, like other statistics students, acquire a firm foundation in statistics and probability, with a program of study similar to those above. These programs have additional requirements as well. Interested students should consult with the graduate advisor of these programs. 

Starting in the Fall of 2019, PhD students are required in their first year to take four semesters of the core PhD courses. Students intending to specialize in Probability, however, have the option to substitute an advanced mathematics class for one of these four courses. Such students will thus be required to take Stat 205A/B in the first year,  at least one of Stat 210A/B or Stat 215A/B in the first year, in addition to an advanced mathematics course. This substitute course will be selected in consultation with their faculty mentor, with some possible courses suggested below. Students arriving with advanced coursework equivalent to that of 205AB can obtain permission to substitute in other advanced probability and mathematics coursework during their first year, and should consult with the PhD committee for such a waiver.

During their second and third years, students with a probability focus are expected to take advanced probability courses (e.g., Stat 206 and Stat 260) to fulfill the coursework requirements that follow the first year. Students are also expected to attend at least one departmental seminar per week, usually the probability seminar. If they are not sufficiently familiar with measure theory and functional analysis, then they should take one or both of Math 202A and Math 202B. Other recommended courses from the department of Mathematics or EECS include:

Math 204, 222 (ODE, PDE) Math 205 (Complex Analysis) Math 258 (Classical harmonic analysis) EE 229 (Information Theory and Coding) CS 271 (Randomness and computation)

The Qualifying Examination 

The oral qualifying examination is meant to determine whether the student is ready to enter the research phase of graduate studies. It consists of a 50-minute lecture by the student on a topic selected jointly by the student and the thesis advisor. The examination committee consists of at least four faculty members to be approved by the department.  At least two members of the committee must consist of faculty from the Statistics and must be members of the Academic Senate. The chair must be a member of the student’s degree-granting program.

Qualifying Exam Chair. For qualifying exam committees formed in the Fall of 2019 or later, the qualifying exam chair will also serve as the student’s departmental mentor, unless a student already has two thesis advisors. The student must select a qualifying exam chair and obtain their agreement to serve as their qualifying exam chair and faculty mentor. The student's prospective thesis advisor cannot chair the examination committee. Selection of the chair can be done well in advance of the qualifying exam and the rest of the qualifying committee, and because the qualifying exam chair also serves as the student’s departmental mentor (unless the student has co-advisors), the chair is expected to be selected by the beginning of the third year or at the beginning of the semester of the qualifying exam, whichever comes earlier. For more details regarding the selection of the Qualifying Exam Chair, see the "Mentoring" tab.  

Paperwork and Application. Students at the point of taking a qualifying exam are assumed to have already found a thesis advisor and to should have already submitted the internal departmental form to the Graduate Student Services Advisor ( found here ).  Selection of a qualifying exam chair requires that the faculty member formally agree by signing the internal department form ( found here ) and the student must submit this form to the Graduate Student Services Advisor.  In order to apply to take the exam, the student must submit the Application for the Qualifying Exam via CalCentral at least three weeks prior to the exam. If the student passes the exam, they can then officially advance to candidacy for the Ph.D. If the student fails the exam, the committee may vote to allow a second attempt. Regulations of the Graduate Division permit at most two attempts to pass the oral qualifying exam. After passing the exam, the student must submit the Application for Candidacy via CalCentral .

The Doctoral Thesis

The Ph.D. degree is granted upon completion of an original thesis acceptable to a committee of at least three faculty members. The majority or at least half of the committee must consist of faculty from Statistics and must be members of the Academic Senate. The thesis should be presented at an appropriate seminar in the department prior to filing with the Dean of the Graduate Division. See Alumni if you would like to view thesis titles of former PhD Students.

Graduate Division offers various resources, including a workshop, on how to write a thesis, from beginning to end. Requirements for the format of the thesis are rather strict. For workshop dates and guidelines for submitting a dissertation, visit the Graduate Division website.

Students who have advanced from candidacy (i.e. have taken their qualifying exam and submitted the advancement to candidacy application) must have a joint meeting with their QE chair and their PhD advisor to discuss their thesis progression; if students are co-advised, this should be a joint meeting with their co-advisors. This annual review is required by Graduate Division.  For more information regarding this requirement, please see  https://grad.berkeley.edu/ policy/degrees-policy/#f35- annual-review-of-doctoral- candidates .

Teaching Requirement

For students enrolled in the graduate program before Fall 2016, students are required to serve as a Graduate Student Instructor (GSI) for a minimum of 20 hours (equivalent to a 50% GSI appointment) during a regular academic semester by the end of their third year in the program.

Effective with the Fall 2016 entering class, students are required to serve as a GSI for a minimum of two 50% GSI appointment during the regular academic semesters prior to graduation (20 hours a week is equivalent to a 50% GSI appointment for a semester) for Statistics courses numbered 150 and above. Exceptions to this policy are routinely made by the department.

Each spring, the department hosts an annual conference called BSTARS . Both students and industry alliance partners present research in the form of posters and lightning talks. All students in their second year and beyond are required to present a poster at BSTARS each year. This requirement is intended to acclimate students to presenting their research and allow the department generally to see the fruits of their research. It is also an opportunity for less advanced students to see examples of research of more senior students. However, any students who do not yet have research to present can be exempted at the request of their thesis advisor (or their faculty mentors if an advisor has not yet been determined).

Mentoring for PhD Students

Initial Mentoring: PhD students will be assigned a faculty mentor in the summer before their first year. This faculty mentor at this stage is not expected to be the student’s PhD advisor nor even have research interests that closely align with the student. The job of this faculty mentor is primarily to advise the student on how to find a thesis advisor and in selecting appropriate courses, as well as other degree-related topics such as applying for fellowships.  Students should meet with their faculty mentors twice a semester. This faculty member will be the designated faculty mentor for the student during roughly their first two years, at which point students will find a qualifying exam chair who will take over the role of mentoring the student.

Research-focused mentoring : Once students have found a thesis advisor, that person will naturally be the faculty member most directly overseeing the student’s progression. However, students will also choose an additional faculty member to serve as a the chair of their qualifying exam and who will also serve as a faculty mentor for the student and as a member of his/her thesis committee. (For students who have two thesis advisors, however, there is not an additional faculty mentor, and the quals chair does NOT serve as the faculty mentor).

The student will be responsible for identifying and asking a faculty member to be the chair of his/her quals committee. Students should determine their qualifying exam chair either at the beginning of the semester of the qualifying exam or in the fall semester of the third year, whichever is earlier. Students are expected to have narrowed in on a thesis advisor and research topic by the fall semester of their third year (and may have already taken qualifying exams), but in the case where this has not happened, such students should find a quals chair as soon as feasible afterward to serve as faculty mentor.

Students are required to meet with their QE chair once a semester during the academic year. In the fall, this meeting will generally be just a meeting with the student and the QE chair, but in the spring it must be a joint meeting with the student, the QE chair, and the PhD advisor. If students are co-advised, this should be a joint meeting with their co-advisors.

If there is a need for a substitute faculty mentor (e.g. existing faculty mentor is on sabbatical or there has been a significant shift in research direction), the student should bring this to the attention of the PhD Committee for assistance.

PhD Student Forms:

Important milestones: .

Each of these milestones is not complete until you have filled out the requisite form and submitted it to the GSAO. If you are not meeting these milestones by the below deadline, you need to meet with the Head Graduate Advisor to ask for an extension. Otherwise, you will be in danger of not being in good academic standing and being ineligible for continued funding (including GSI or GSR appointments, and many fellowships). 

†Students who are considering a co-advisor, should have at least one advisor formally identified by the end of the second year; the co-advisor should be identified by the end of the fall semester of the 3rd year in lieu of finding a Research Mentor/QE Chair.

Expected Progress Reviews: 

* These meetings do not need to be held in the semester that you take your Qualifying Exam, since the relevant people should be members of your exam committee and will discuss your research progress during your qualifying exam

** If you are being co-advised by someone who is not your primary advisor because your primary advisor cannot be your sole advisor, you should be meeting with that person like a research mentor, if not more frequently, to keep them apprised of your progress. However, if both of your co-advisors are leading your research (perhaps independently) and meeting with you frequently throughout the semester, you do not need to give a fall research progress report.

• Graduate Studies

Ph.D. Program

The PhD program prepares students for research careers in theory and application of probability and statistics in academic and non-academic (e.g., industry, government) settings.  Students might elect to pursue either the general Statistics track of the program (the default), or one of the four specialized tracks that take advantage of UW’s interdisciplinary environment: Statistical Genetics (StatGen), Statistics in the Social Sciences (CSSS), Machine Learning and Big Data (MLBD), and Advanced Data Science (ADS). 

Admission Requirements

For application requirements and procedures, please see the graduate programs applications page .

Recommended Preparation

The Department of Statistics at the University of Washington is committed to providing a world-class education in statistics. As such, having some mathematical background is necessary to complete our core courses. This background includes linear algebra at the level of UW’s MATH 318 or 340, advanced calculus at the level of MATH 327 and 328, and introductory probability at the level of MATH 394 and 395. Real analysis at the level of UW’s MATH 424, 425, and 426 is also helpful, though not required. Descriptions of these courses can be found in the UW Course Catalog . We also recognize that some exceptional candidates will lack the needed mathematical background but succeed in our program. Admission for such applicants will involve a collaborative curriculum design process with the Graduate Program Coordinator to allow them to make up the necessary courses. 

While not a requirement, prior background in computing and data analysis is advantageous for admission to our program. In particular, programming experience at the level of UW’s CSE 142 is expected.  Additionally, our coursework assumes familiarity with a high-level programming language such as R or Python. 

Graduation Requirements 

This is a summary of the department-specific graduation requirements. For additional details on the department-specific requirements, please consult the  Ph.D. Student Handbook .  For previous versions of the Handbook, please contact the Graduate Student Advisor .  In addition, please see also the University-wide requirements at  Instructions, Policies & Procedures for Graduate Students  and  UW Doctoral Degrees .  

General Statistics Track

• Core courses: Advanced statistical theory (STAT 581, STAT 582 and STAT 583), statistical methodology (STAT 570 and STAT 571), statistical computing (STAT 534), and measure theory (either STAT 559 or MATH 574-575-576).  
• Elective courses: A minimum of four approved 500-level classes that form a coherent set, as approved in writing by the Graduate Program Coordinator.  A list of elective courses that have already been pre-approved or pre-denied can be found here .
• M.S. Theory Exam: The syllabus of the exam is available here .
• Research Prelim Exam. Requires enrollment in STAT 572. 
• Consulting.  Requires enrollment in STAT 599. 
• Applied Data Analysis Project.  Requires enrollment in 3 credits of STAT 597. 
• Statistics seminar participation: Students must attend the Statistics Department seminar and enroll in STAT 590 for at least 8 quarters. 
• Teaching requirement: All Ph.D. students must satisfactorily serve as a Teaching Assistant for at least one quarter. 
• General Exam. 
• Dissertation Credits.  A minimum of 27 credits of STAT 800, spread over at least three quarters. 
• Passage of the Dissertation Defense. 

Statistical Genetics (StatGen) Track

Students pursuing the Statistical Genetics (StatGen) Ph.D. track are required to take BIOST/STAT 550 and BIOST/STAT 551, GENOME 562 and GENOME 540 or GENOME 541. These courses may be counted as the four required Ph.D.-level electives. Additionally, students are expected to participate in the Statistical Genetics Seminar (BIOST581) in addition to participating in the statistics seminar (STAT 590). Finally, students in the Statistics Statistical Genetics Ph.D. pathway may take STAT 516-517 instead of STAT 570-571 for their Statistical Methodology core requirement. This is a transcriptable program option, i.e., the fact that the student completed the requirements will be noted in their transcript.

Statistics in the Social Sciences (CSSS) Track

Students in the Statistics in the Social Sciences (CSSS) Ph.D. track  are required to take four numerically graded 500-level courses, including at least two CSSS courses or STAT courses cross-listed with CSSS, and at most two discipline-specific social science courses that together form a coherent program of study. Additionally, students must complete at least three quarters of participation (one credit per quarter) in the CS&SS seminar (CSSS 590). This is not a transcriptable option, i.e., the fact that the student completed the requirements will not be noted in their transcript.

Machine Learning and Big Data Track

Students in the Machine Learning and Big Data (MLBD) Ph.D. track are required to take the following courses: one foundational machine learning course (STAT 535), one advanced machine learning course (either STAT 538 or STAT 548 / CSE 547), one breadth course (either on databases, CSE 544, or data visualization, CSE 512), and one additional elective course (STAT 538, STAT 548, CSE 515, CSE 512, CSE 544 or EE 578). At most two of these four courses may be counted as part of the four required PhD-level electives. Students pursuing this track are not required to take STAT 583 and can use STAT 571 to satisfy the Applied Data Analysis Project requirement. This is not a transcriptable option, i.e., the fact that the student completed the requirements will not be noted in their transcript. 

Advanced Data Science (ADS) Track

Students in the Advanced Data Science (ADS) Ph.D. track are required to take the same coursework as students in the Machine Learning and Big Data track. They are also not required to take STAT 583 and can use STAT 571 to satisfy the Applied Data Analysis Project requirement. The only difference in terms of requirements between the MLBD and the ADS tracks is that students in the ADS track must also register for at least 4 quarters of the weekly eScience Community Seminar (CHEM E 599). Also, unlike the MLBD track, the ADS is a transcriptable program option, i.e., the fact that the student completed the requirements will be noted in their transcript. 

Department of Statistics

Handbook for phd students in statistics.

TABLE OF CONTENTS

• Introduction
• Incoming Students
• Course Registration
• First Year Course Requirements and Preliminary Examinations
• Second Year Requirements
• Third Year Requirements
• Fourth Year Requirements
• Fifth Year and Beyond
• Dissertation Defense and Submission
• Consulting Program
• Academic Year Student Support and Teaching Duties
• Summer Support
• Off Campus Work
• Student Representatives
• Student Offices
• Reimbursements

INTRODUCTION

Dear Students,

We have compiled this manual summarizing all the rules, requirements and deadlines governing the PhD program in the Statistics Department. We intend this manual to be the primary repository of these rules and we encourage you to refer to it periodically as you progress through our program. If you have any questions regarding the content you are welcome to contact the Department Graduate Advisor (Yali Amit) or the Student Affairs Specialist (Keisha Prowoznik).

Good luck with your studies!

INCOMING STUDENTS

• New Graduate Student Information–UChicago Grad: Information regarding the University of Chicago campus, living in the neighborhood, security, health, and other resources for incoming graduate students can be found here: https://grad.uchicago.edu/life-at-uchicago/admitted-students-welcome/
• Diagnostic Exam: A diagnostic exam will be emailed to all students the week before orientation to be returned to their advisor by the end of that week in order to help determine which courses to take for the upcoming year.
• Orientation: This event will take place on the week before classes start where new students will attend meetings throughout campus and the Department to become acclimated with procedures and guidelines for the PhD program. This is also course registration week, where all students will have to meet with their advisor to determine which courses to take during Autumn quarter. Incoming students will meet with the Department Graduate Advisor (DGA) for course registration.

COURSE REGISTRATION

Course registration starts the Monday of the 8th week of every quarter when the Student Affairs Specialist sends out an email to all students with the attached registration form for each student to fill out, and gain consent from their advisor and return back to the Student Affairs Specialist. Students must register themselves and if they cannot, they can seek help from the Student Affairs Specialist. All course registration must be completed the Friday of 10th week by 12:00PM Central Standard Time in order to avoid a late fee.

Drop/add week will always take place the first week of every quarter and run for three weeks and end on the Friday of third week for all PhD students. This is a time where students are able to drop and/or add courses to their schedule if they do not wish to take the courses they registered for during course registration week. Courses can be changed upon the advisor and instructor’s approval.

FIRST YEAR COURSE REQUIREMENTS AND PRELIMINARY EXAMINATIONS

The program offers four core sequences:

• Probability (STAT 30400, 38100, 38300)
• Mathematical statistics (STAT 30400, 30100, 30210)
• Applied statistics (STAT 34300, 34700, 34800 and 34900)
• Computational sequence (STAT 30900, 31015/31020, 37710).

All students must take the Applied Statistics and Mathematical Statistics sequence. In addition, it is highly recommended that students take a third core sequence based on their interests and in consultation with the Department Graduate Advisor (DGA).

Preliminary exams: At the start of their second year, several weeks before the start of the Fall quarter , the students take two preliminary examinations. The students will be informed by June 1 of the precise dates. All students must take the Applied Statistics Prelim. The prelim is a take-home exam provided online to the students during  prelim week. Student written reports are handed in two days later. A few days later, after the faculty review the reports the students have a 30 minute oral interview about their report.

For the second prelim, students can choose to take either the Theoretical Statistics or the Probability prelim. Students planning to take the Probability prelim should take the Probability sequence as their third first year course sequence and must receive approval from the DGA to take 38300 in the Spring instead of 348.  

During six weeks leading up to the prelims, two advanced PhD students will assist the first year students in preparing for the exams, holding weekly meetings one for the Applied Statistics exam and one for the Theoretical Statistics exam.

Incoming first-year students may request the DGA to take one or both of their preliminary exams. This will only be considered if the students have had extensive training in statistics in their prior studies. If approved, and if the student passes one or more of these, then he/she may be excused from the requirement of taking the first-year courses in that subject.

First year summer reading courses: It is highly recommended for first year students to take a reading course with a faculty member during the summer. This does not require formal registration, only coordination with a faculty member. Such a reading course typically involves reading a number of papers recommended by the faculty member and presenting them during the meetings.

Incoming students are advised by the DGA until they find a faculty advisor for their PhD thesis work.

First year students also share responsibility for organizing lunches with faculty to hear about their research, lunches with visiting seminar speakers and weekly departmental tea time.

SECOND YEAR REQUIREMENTS

In their second year, PhD students typically take several advanced topics courses in statistics, probability, computation, and applications. These should be selected with the dual objective of (i) acquiring a broad overview of current research areas, and (ii) settling on a particular research topic and dissertation supervisor. It is recommended that the students take at least one regular class based course each quarter. In addition, students can ask to take reading courses with faculty to learn more in depth about their fields of research. Students have considerable latitude in selecting their second-year courses, but their programs must be approved by the Department Graduate Advisor.  Students are expected to find a dissertation/thesis advisor by the end of the second year. The thesis advisor does not need to be a faculty member of the Statistics Department, however the dissertation/thesis committee must include at least two members of the Statistics Department (see below.)

Mini-seminars: During the second half of Spring Quarter second year students are required to give a short 10-12 minute presentation on a paper/papers they have read, followed by a short Q & A period. This provides the students with their first experience giving a presentation and both faculty and other students can provide feedback. The students typically present papers they have read in one of the reading courses they have taken with a faculty member during the second year.

THIRD YEAR REQUIREMENTS

Thesis Advisor and Dissertation Committee

By the end of the third year, each PhD student, after consultation with his or her dissertation advisor, shall establish a committee of at least three members, at least two of whom should be from Statistics. The departmental form listing the committee members, with their signatures, must be filed in the Department office by the end of Spring Quarter of the third year. The composition of the committee may be changed at any time if the student or faculty so choose; however, it must always include the student's dissertation advisor and at least two of the committee members must be regular faculty members from the Department of Statistics. Any such change must be filed as a resubmitted and newly completed and signed form with the Department office. As long as a student has not found a thesis advisor the DGA will remain the student’s advisor.

Interdisciplinary Theses

Many of our students choose to pursue research combining statistics and computation with another area of scientific research, such as genetics, neuroscience, health studies, environmental science, or social science. Students who choose to write an interdisciplinary thesis can work with a thesis advisor from another department as long as the two other committee members are from the Statistics Department.

FOURTH YEAR REQUIREMENTS

Proposal Presentation and Admission to Candidacy

By the end of Autumn Quarter of the fourth year, students should have completed a proposal presentation to their committee. This consists of a written (typically 5-10 page) report on completed and planned research with relevant references and a meeting with the committee discussing the proposed research (format is flexible, but typically a 1.5 hour meeting, with 45 minutes for student presentation and 45 minutes for questions and discussion). The proposal meeting will be scheduled by the student and his or her committee and reported to the Department office. Acceptance of the proposal by the Dissertation Committee is a formal requirement of the Department's PhD program. After a successful proposal presentation, the student will be formally admitted to candidacy for the PhD degree. By University rules, the dissertation defense cannot occur earlier than 8 months after admission to candidacy, and the student should keep this in mind when scheduling both the proposal presentation and the defense.

Following the fourth year, during each year that the student remains, the student is required to have a meeting with the committee no later than November 30 th of Autumn Quarter or defend by that time.

FIFTH YEAR AND BEYOND

The Department goal is for the majority of students to complete and defend their thesis by the end of their 5th year. Foreign students will have their visas extended beyond the fifth year on a yearly basis depending on the decision of the committee.

In the first 4 weeks of the Fall quarter of the 5th year students should convene their Dissertation Committee for an update on their progress. Committee members will confirm satisfactory progress on a form provided by the Department office.

Students who have not completed their thesis by the end of Fifth year must petition their committee and the Department Chair in order to continue in the program into their Sixth year and maintain their stipend. If their petition is  approved and they are not supported as RA’s they  will be required to teach every quarter.

Students who continue to their 6th year should again  convene their Dissertation Committee in the first 4 weeks of the Fall quarter  of the 6th year and Committee members will confirm satisfactory progress on a form provided by the Department office.

Students who have not completed their dissertation and defense by the end of the sixth year will no longer receive stipends or be employed by the Department. These students are required to petition their committee and the Department Chair both in order to continue in the doctoral program and for any financial support (tuition, fees). The petition is to be made before the end of Spring Quarter of the sixth year.

DISSERTATION DEFENSE AND SUBMISSION

The PhD degree will be awarded following a successful defense and the electronic submission of the final version of the dissertation to the University's Dissertation Office. In this process, a number of University and Department deadlines have to be obeyed. Listed in reverse order, the steps are:

a) Submission of Final Version of Dissertation: The deadline is set by the University and is generally on a Friday in the 6th or 7th week of the quarter when the degree will be awarded. See:

• Information for PhD Students: https://www.lib.uchicago.edu/research/scholar/phd/students/
• Dissertation Deadlines: https://www.lib.uchicago.edu/research/scholar/phd/students/dissertation-deadlines/
• Information about dissertations: https://www.lib.uchicago.edu/research/scholar/phd/students/
• Latex template for dissertation: https://www.overleaf.com/latex/templates/university-of-chicago-phd-dissertation-template/syvxgkqhvqqt

for this deadline as well as guidelines for the formatting of dissertations.

b) Dissertation Defense: The thesis defense will be an open seminar announced to the Department. Following the regular question-and-answer session, the committee will remain, together with any interested faculty, and continue questioning the candidate. The decision on the thesis will then be reached in a closed meeting of the dissertation committee. The defense is to be scheduled at least two weeks before the University deadline indicated in point (a). A final draft of the dissertation must be made available to the entire faculty 8 days before the dissertation presentation.

c) Committee Approval of Scheduled Defense: A draft of the dissertation should be distributed to the members of the dissertation committee no later than five weeks before the dissertation defense. The committee then has two weeks to approve that the student can reasonably expect to defend the thesis, and three more weeks to fully assess.

These rules delineate the minimum level of involvement of the dissertation committee. We strongly recommend that students set up their committees early and that they interact regularly with the members of their committees once they are established. We strongly recommend that those students wishing to complete all degree requirements, including their defense, by the end of Summer quarter contact their committee to schedule their Summer defense date before Summer Quarter begins. Else unanticipated committee requirements may lead to the degree being delayed to the Winter Quarter.

CONSULTING PROGRAM

The Department runs a consulting for training purposes, at the same time providing a service for researchers in other departments in the University. Students serve as the consultants, working as the quantitative expert in statistics alongside the researchers. Two faculty members lead the consulting program. The consulting seminar meets once a week for an hour during academic quarters. In these meetings researchers may present a problem, the students may present their projects, or some interesting applied case study may be analyzed. The students rotate weekly through consulting `office hours', which are the times when researchers can approach with their requests. Typically, four to six graduate students work together as a team under the supervision of faculty members to address these requests.  The teams share their experience by presenting their analysis to the seminar. Students are required to register for the consulting program for two quarters each of years 1 through 3. Third year students can delay one of their consulting quarters to their fourth year.

ACADEMIC YEAR STUDENT SUPPORT AND TEACHING DUTIES

PhD students are guaranteed support for five years and in return are required to work as teaching assistants (TAs) for two quarters of each year and on one quarter they are off. Incoming first year students  are all off during the first quarter. TA assignments are determined 3-4 weeks prior to the start of the quarter, at which point the students are required to contact the faculty member teaching the course for instructions on their upcoming duties. Students may request the DGA to assign them to particular courses, or ask to have a particular quarter off. There is no guarantee that these requests will be satisfied, but the DGA does take them into account. Students are not allowed to work as TA's for any other University unit during their off quarter.

Research Assistants (RAs): Faculty members may decide to support their student  from a grant in one or more of their teaching quarters. In those quarters the students are not required to perform TA duties. Students can receive RA support from faculty advisors outside the Department.

Instructorship: Some students may be asked to be instructors in introductory Statistics courses, especially during the Spring quarter. These students receive a bonus in their summer support (at time of writing, July 2022, this is 2000 USD). The DGA determines which students are suitable for such positions.

Sixth year students and beyond: Students who have not completed their dissertation by the end of the fifth year must, by the end of Spring Quarter, obtain permission from their committee and the Department Chair to continue beyond the fifth year. If they are allowed to continue but are not hired as RA’s they will be funded by the Department, but  required to teach every quarter. Students who have not completed their dissertation and defense by the end of the sixth year will no longer receive stipends or be employed by the Department. These students are required to petition the Department both in order to continue in the doctoral program and for any financial support (tuition, fees). This petition is to be made to both their committee and the Department Chair before the end of Spring Quarter of the sixth year.

Quarterly Funding Letters: A few weeks before every quarter the Student Affairs Specialist will send out the quarterly funding letter which will list each students’ position (TA, Instructor, RA, OFF) for the upcoming quarter. This letter will also list stipend or paycheck dates depending on the students’ position and an itemized amount of costs for the quarter and who is responsible for the payment. This letter is very important in that it will tell the student if they will hold a position that quarter and what date/dates they will be paid.  

SUMMER SUPPORT

Students are provided with full 3 month summer support during their first 4 years. Support during the fifth summer is contingent on approval of the advisor and the Chair.

Internships: Students can choose to take on internships during the summer, in which case they forfeit the departmental summer support. The decision on whether to take an internship and which ones are appropriate are taken in consultation with the student's thesis advisor. It is not recommended to take internships before finding a thesis advisor.

OFF CAMPUS WORK

Students in a full-time registration status are expected to focus their attention and efforts principally on their academic work and additional employment is secondary to their student status. A domestic student wanting to take off-campus employment will typically need to take a leave of absence from the program. For international PhD students, OIA recently introduced a version of CPT (CPT RCOT) that may allow them to work off-campus outside of summer. [see https://internationalaffairs.uchicago.edu/page/curricular-practical-training-cpt ]. However, this requires approval by the PSD Dean of Students, and will involve careful consideration of a number of factors. Moreover, the Dean of Students views this mechanism as intended for only very short-term off-campus work (eg 1 quarter) and not for long term. Repeated enrollment in CPT RCOT will generally not be approved by the Dean of Students. Students who have questions about CPT RCOT should direct them to the PSD Dean of Students.

Note: work at Argonne national labs is excepted from usual "off-campus" regulations due to an agreement between Argonne and UChicago.

STUDENT REPRESENTATIVES

During the first week of Fall quarter the PhD students gather to elect a student representative(s), who are responsible for communicating with the DGA and the Chair regarding any issues arising among the student body. They are also asked on occasion to coordinate student social activities such as the annual picnic. The Departmental Student Affairs Specialist assists the student representatives with any administrative tasks associated with their duties.

STUDENT OFFICES

All keys for student offices will be given during orientation week in the Student Affairs office. 1st year PhD students will always have desks in Jones 208, 2nd-4th year students will have desks in Jones 203/204, and 5th and 6th year students will have desks in Jones 209. Students will sign a key check-out form which states they will be responsible for their desk key of $20 and the office key of $30 and if they lose the key they must pay the Department either of the amounts in order to obtain a new key.

REIMBURSEMENTS

Students who wish to travel throughout the year for conferences that are sponsored on a grant or research funds from their advisor can be reimbursed by the Student Affairs Specialist with detailed receipts and confirmation that this trip has been approved and sponsored by the advisor/faculty member.

In case the advisor is unable to support the student travel but still approves it, the student may petition the Department Chair for up to $1000 of Departmental support.

PhD in Statistics

The Doctor of Philosophy (PhD) program in Statistics is designed to prepare you to work on the frontiers ofthe discipline of Statistics, whether your career choice leads you into research and teaching or into leadership roles in business, industry and government.

The program is very flexible particularly in the choice of electives and of research topic. You may even choose to do research on the interface of Statistics and some other discipline, such as Computer Science, Genetics, Forestry, Bioinformatics, Economics, etc. The course requirements are designed to ensure that you have sufficient training in Probability, Statistical Inference, Computing, and Applications to prepare you for research on the cutting edge of Statistics.

Many items in this section, with some modifications for the Department’s purposes, are taken from the Graduate Bulletin .

Prerequisite and Application Information

Guidelines for PhD Program 

Detailed Program Information

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Jaxk Reeves Graduate Coordinator I [email protected]

Liang Liu Graduate Coordinator II [email protected]

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Statistics & Data Science

Dietrich college of humanities and social sciences, ph.d. programs, our ph.d. programs enable students to pursue a wide range of research opportunities, including constructing and implementing advanced methods of data analysis to address crucial cross-disciplinary questions, along with developing the fundamental theory that supports these methods..

Unique opportunities for our Ph.D. students include:

• We host four cross-disciplinary joint Ph.D. programs for students who want to specialize in machine learning , public policy , neuroscience , and the link between engineering and policy .
• Our faculty have deep involvement in a range of important, data-rich scientific collaborations, including in the areas of genetics, neuroscience, astronomy, and the social sciences. This allows students to have easy access to both the crucial questions in these fields, and to the data that can provide the answers.
• Students begin work on their Advanced Data Analysis Project in the second semester. This year-long, faculty/student collaboration, distinct from the thesis, provides an immediate intensive research experience.
• Carnegie Mellon is home to the first Machine Learning Department . Many of our faculty maintain joint appointments with this Department and they (and our students) have strong connections to this exciting and growing area of research.

The programs leading to the degree of   Doctor of Philosophy in Statistics   seek to strike a balance between theoretical and applied statistics. The Ph.D. program prepares students for university teaching and research careers, and for industrial and governmental positions involving research in new statistical methods. Four to five years are usually needed to complete all requirements for the Ph.D. degree.

These pages present the requirements for each of our Ph.D. programs.

The page   "Core Ph.D. Requirements"   lays out the requirements for all Ph.D. students, while each of the four joint programs are described under the Joint Ph.D. Degrees pages. Our Ph.D. students can also earn a   Master of Science in Statistics   as an intermediate step towards their ultimate goal.

Joint Ph.D. Programs

Statistics/machine learning, statistics/public policy, statistics/engineering and public policy, statistics/neural computation  .

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The Ph.D. in Statistics is flexible and allows students to pursue a variety of directions, ranging from statistical methodology and interdisciplinary research to theoretical statistics and probability theory. Students typically start the Ph.D. program by taking courses and gradually transition to research that will ultimately lead to their dissertation, the most important component of the Ph.D. program.

These requirements apply to students admitted for Fall 2020 and after. Students admitted in Fall 2019 and earlier should consult the Previous Program Requirements page .

PhD Coursework:

The core PhD curriculum is divided into five areas: 

Methods — STATS 600 and 601

Practice — STATS 604

Statistical Theory — STATS 511, 610, 611

Probability — STATS 510, 620, 621

Computing — STATS 507, 606, 608 

All doctoral students must complete the following in their first three semesters in the program and before advancing to candidacy: 

Take all methods and practice courses (600, 601, 604)

Take at least two courses in the combined areas of statistical theory and probability,  including at least one course in statistical theory and at least one 600-level course 

Take at least one computing course

Achieve a 3.5 average grade (on the 4.0 scale used by Rackham) in 600, 601, 604, and one 600-level statistical theory or probability course

Not completing requirements 1-4 by the end of the third semester will trigger probation which, if not resolved by the end of the fourth semester, may lead to dismissal from the program.  For more details, see the link below. 

By the end of the PhD program, all students must take at least 30 credits of graduate statistics courses.    All courses from the core areas count towards this total, as well as all 600-level, 700-level, and selected additional  500-level courses with approval of the PhD Program Director. Seminars and independent study courses do not count. At least 21 credits must be at the 600 level or higher. The Rackham Graduate School requires PhD students to maintain an overall GPA of at least 3.0 to remain in good standing.   

In addition, all doctoral  students must take 3 credits of cognate courses as required by the Rackham graduate school, and two professional development seminar courses. Cognate courses are 400- and higher-level courses from outside Statistics and not cross-listed with Statistics. All cognate course selections must be approved by the PhD Program Director. The professional development courses are 

STATS 810, research ethics and introduction to research tools, in the first semester in the program.

STATS 811, technical writing in statistics. Students are strongly advised to complete this course in their second or third year.

Typical Course Schedules:

Our Ph.D. program admits students with diverse academic backgrounds. All PhD students take STATS 600/601  in their first year. Students are strongly encouraged to take STATS 604 in their second year (Stats 600 is a prerequisite).  

Students with less mathematical preparation typically take STATS 510/511 (the Master’s level probability and statistical theory) in their first year and 600-level probability and/or statistical theory courses in their second year.    

Advanced students, for example those with a Master’s degree, typically do not need to take 510/511, and in some cases may skip 610 and 621. Students who wish to take 600-level probability and statistical theory courses in their first year must take a placement test just before the fall semester of their first year to get approved. The PhD Program Director will help each student choose their individual path towards completing the requirements.  

Some typical sample schedules are listed below. In most cases, we do not recommend taking more than three full-load courses per semester (not counting seminars).

Sample schedule 1:

Sample schedule 2:

Advancing to Candidacy:

Students are expected to find a faculty advisor and start research leading to their dissertation proposal no later than the summer after their first year. The PhD Program Director and the faculty mentor assigned to each first year student can assist with finding a faculty advisor. Students are expected to submit a dissertation proposal and advance to candidacy some time during their second or third year in the program.   

Requirements for advancing to candidacy are:

Satisfying Requirements 1-4

Completing at least 3 credit hours of cognate courses

Writing a dissertation proposal and passing the oral preliminary exam, which consists of presenting the proposal to the student's preliminary thesis committee

A dissertation proposal should identify an interesting research problem, provide motivation for studying it, review the relevant literature, propose an approach for solving the problem​, and present at least some preliminary results​. The written proposal must be submitted to the preliminary thesis committee a​head of time (one week minimum, two weeks recommended)​ and then presented in the oral preliminary exam. The preliminary thesis committee is chaired by the faculty advisor and must include at least two more faculty members, at least one of them from Statistics. ​​The faculty on the preliminary thesis committee typically continue t​o serve ​on ​the doctoral thesis committee​​, but changes are allowed.  Please see Rackham rules on thesis committees for more information.  

At the oral preliminary exam, the committee will ask questions about the proposal and the relevant background and either elect to accept the proposal as both substantial and feasible, ask for specific revisions, or decline the proposal. The unanimous approval of the proposal by the committee is necessary for the student to advance to candidacy.

Additional Information:

Students are encouraged to complete the bulk of their coursework beyond Requirements 1-4 in the first two years of study.  Candidates are allowed to take only one course per semester without an increase in tuition.

All PhD students are expected to register for Stats 808/809  (Department Seminar) every semester unless restricted by candidacy, and attend the seminar regularly regardless of whether they are registered.  

Exceptions to the PhD program requirements may be granted by the PhD Program Director.

Annual Report:

Each candidate is required to meet with the members of their thesis committee annually. This could be in the form of either giving a short presentation on their research progress to the thesis committee as a group, or meeting with committee members individually.

Each committee member should complete a Thesis Committee Member Report and return it to the student. The student should share the completed Thesis Committee Member Reports with both the PhD Program Coordinator and their advisor.

All meetings with the committee members should take place by April 15.

Following the meetings, the student and the advisor should complete the Annual PhD Candidate Self-Evaluation and Feedback Form . The advisor should review the committee members’ Thesis Committee Member Reports and take them into account when completing the advisor’s portion. The completed Annual PhD Candidate Self-Evaluation and Advisor Feedback Form must be submitted to the PhD Program Coordinator by May 31. The completed form will be saved with the department, and a copy will be shared with the student.

Dissertation and Defense:

Each doctoral student is expected to write a dissertation that makes a substantial and original contribution to statistics or a closely related field. This is the most important element of the doctoral program. After advancing to candidacy, students are expected to focus on their thesis research under the supervision of the thesis advisor and the doctoral committee. The composition of the doctoral committee must follow the Rackham's  guidelines for dissertation committee service . The written dissertation is submitted to the committee for evaluation and presented in an oral defense open to the public.

Rackham Requirements:

The Rackham Graduate School imposes some additional requirements concerning residency, fees, and time limits. Students are expected to know and comply with these requirements.

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PhD Program

The PhD Statistics program provides excellent training in the modern theory, methods, and applications of statistics to prepare for research and teaching careers in academia or industry, including interdisciplinary research in a wide array of disciplines. The median time to degree is five years.

Students will take courses in modern theory, methods, and applications of statistics, demonstrate mastery of this material via a qualifying examination, and then conduct statistical research under the supervision of one of the many regular or affiliate faculty members in the department, resulting in a dissertation.

The PhD qualifying examination is primarily based on the first-year curriculum. Most students pass at the end of the summer after the first year of the program. Students select between two versions of the examination, one with questions from mathematical statistics and probability or the second with questions from mathematical statistics and statistical methods.

Graduates are prepared for positions in academia, business, or government. They have taken positions at leading universities such as UC-Berkeley, Penn, and Yale and at top companies such as Google, Facebook, and Eli Lilly. The department strives to support students in the PhD program as teaching, research, or project assistants.

Questions about our Statistics PhD Programs can be directed to our graduate program coordinator at  [email protected] .

Resources, Regulations, and Policies

• Statistics PhD Handbook 2024-2025 More
• Criteria for Satisfactory Progress More
• Current PhD Regulations More
• 2014 PhD Regulations More

PhD Statistics Program Options

There are two program options students can select from – PhD Statistics, Statistics Option or PhD Statistics, Biostatistics Option . 

We have a single admissions process for both options and we encourage applicants to select only one of the options and not list both when applying. Selection of the program to which you apply has very little influence on the admissions decision. If you are unsure of which program option to choose, students who enter our PhD program may readily switch between the programs. 

Please note that the Department of Biostatistics and Medical Informatics has a separate PhD program in Biomedical Data Science that is distinct from the programs in the Department of Statistics.

Statistics Option

Career Outcomes : Students will be prepared for research and teaching careers in academia, industry, and other disciplines.

Coursework : Students will take courses in several broad areas of statistical methods and theory. This includes two-semester sequences in mathematical statistics and in statistical methods, either a course in probability theory or a course in statistical computing, a statistical consulting course, and a wide variety of elective options.

Biostatistics Option

Career Outcomes : Students will be prepared for careers in clinical research, genetics, drug testing, and experimental design in academia, government, and private sector.

Coursework : Students in the Biostatistics named option complete the same required courses as are in the Statistics named option, but have additional required coursework in biostatistics and biology and fewer elective course requirements.

Applying to the PhD Statistics Program

The application deadline is December 1 for a fall term start (no spring admissions).   A reminder to only list either the Statistics Option or Biostatistics Option in your application, not both. Again, students who enter the PhD program in Statistics can readily switch between the programs.

We welcome applications from around the world and strive to admit well-qualified applicants who are interested in the diverse array of research interests of our faculty. We do not make preliminary evaluations of any applicant inquiry based on email communication. No decision will be made until after the deadline has passed and a completed file (including the application fee) has been received.

Before applying to the Statistics Department, please read the Graduate School Frequently Asked Questions. Note that there is a non-refundable application fee. Applicants whose native language is not English, or whose undergraduate instruction was not in English, must provide an English proficiency test score.

To be considered for financial assistantship, all required application materials listed below should be submitted via the electronic application at https://apply.grad.wisc.edu/ by the December 1 deadline.

• Letters of Recommendation
• Transcripts
• Statement of Purpose
• CV or Resumé
• Supplemental Application (Including a List of Courses)
• English Proficiency
• A minimum of three (3) letters of recommendation to be submitted electronically by the recommenders.
• The online application for admission asks for the name and email contact information of the references from whom you request recommendations. A recommendation request will be sent, by email, to each of your references. The email will include your name with a link to each department’s electronic recommendation form. The request can be sent at any time providing you meet department deadlines. You can change references or send a reminder through your application.
• It is common practice to contact your references ahead of time so that they expect your request.
• After you have submitted your application, you can view receipt of your recommendations through the online status system.
• As part of the online application, please upload a clear and easy-to-read PDF copy of your transcript from each institution of higher learning (post High School) that you have attended. Unofficial transcripts are acceptable. If we offer you admission, you will be asked to provide an official copy of your transcript to the Graduate School at that time. Admission will be contingent upon receiving the official transcript.
• If courses at the institution were not taught in English, we will need an electronic copy of both the transcript in the original language, and the transcript in English.
• Your statement of purpose should include why you feel that the UW-Madison program is a good fit for you, and conversely, why you are a good fit for our program. What are you hoping to work on in the field with your degree? Are there any professors here that you would particularly like to work with? Any research areas in statistics that particularly excite you?
• The overall length of the statement is usually about 2 pages, single or double spaced. You can use whatever font and formatting you are comfortable with.

Please upload a PDF copy of your CV or Resumé to the online application.

A supplemental application is required as part of the online application. You will be asked to answer the following questions and provide the following information:

• Are you applying to the Biostatistics option? Yes/No (There is no advantage to applying to both programs.)
• List any major competitive honors, awards, and/or fellowships you have received.
• List any undergraduate or graduate research experiences.
• Provide a table with all courses you have taken, are currently taking, or plan to take prior to coming to UW-Madison that contain substantial mathematical, statistical, quantitative, or computational content. Include courses from other disciplines such as economics, physics, or engineering, if applicable. Use one row per course with columns for the course number, course title, textbook used (if possible), and grade received (if already completed). Upload this document as a pdf.

The GRE is not required.

• For all international degree-seeking students, see the  Graduate School requirements page  for additional information.

Consult the Graduate School for general information about graduate admissions to the University of Wisconsin-Madison.

If you have any further questions, please email [email protected] . Please include your full name and what semester you are interested in applying for.

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PhD in Statistics

Phd in statistics program.

The PhD in Statistics prepares students professional leadership in statistical research, teaching and collaboration as faculty at colleges and universities and as researchers at government institutions or in the private sector.

Coursework Requirements

MS in Statistics

Qualifying, Prelim, and Final Exams

Review and Advisory

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PhD Student Handbook

DEPARTMENT OF STATISTICS AND DATA SCIENCE

Phd placements, phd graduates.

The following gives the current employer (if known) of recent PhD graduates. For dissertation titles, please see Graduate Student Research

Joanna (Jiahui) Lyu, 2023 Walmart Inc.

Sebastian Rodriguez, 2022 ZS Consulting

Yajun Liu, 2022 Amazon Wei Ju, 2021 Facebook Mena Whalen, 2021 Assistant Professor, Department of Mathematics and Statistics, Loyola University, Chicago Sarah Peko-Spicer, 2021 Research Analyst, American Institutes for Research Rrita  Zejnullahi , 2021 Assistant Professor, Division of Biostatistics and Epidemiology in the School of Public Health and the College of Applied Health Sciences, University of Illinois Chicago (UIC) Kaitlyn Fitzgerald, 2021 Assistant Professor, Department of Mathematics, Physics, and Statistics, Azusa Pacific University Aaron Kleyn, 2021 Biostatistician, Arcus Biosciences Yiming Xu, 2020 Facebook Oscar Zarate, 2020 Data Scientist, Microsoft Yiben Yang, 2020 Research Scientist, Facebook Yang Yu, 2020 Data Scientist, Facebook Austin Alleman, 2020 Data & Applied Scientist, Microsoft Yuanjing Ma, 2020 Data Scientist, Point72 Asset Management Pan Wang, 2019 Principal Biostatistician, Biogen Ruimin Zhu, 2019 Pinterest Mindy Hong, 2019 Clinical Research Statistician, Hinge Health Minhui Zheng, 2019 Data Scientist, Google Yishu Wei, 2019 Research Scientist, Facebook Wenqian Wang, 2019 Data Scientist, LinkedIn Corporation Yuan Li, 2018 Data scientist , Google, Inc. Bin Xiong, 2018 Assistant Vice President, Citi Jingsi Zhang, 2018 Research Scientist, Amazon Jacob Schauer, 2018 Assistant Professor of Preventive Medicine at Northwestern University’s Feinberg School of Medicine Ran Yang, 2018 Machine Learning Engineer, Facebook Rachel Ktsanes, 2017 PayNet Grace Yoon, 2017 Postdoc, Texas A&M University Xuan Mei, 2017 JP Morgan Chase & Co. Wendy Chan, 2016 Assistant Professor at University of Pennsylvania Yi Gao, 2016 Statistician at Google Xiaofei Hu, 2016 Data Scientist, Twitter Zachary Seeskin, 2016 Statistician at NORC at the University of Chicago Arend M. Kuyper, 2015 Director of Data Science and Assistant Professor of Instruction, Department of Statistics and Data Science, Northwestern University Fengqing (Zoe) Zhang, 2015 Associate Professor in the Department of Psychology at Drexel University College of Arts and Sciences Qingyang Zhang, 2015 Assistant Professor in the Department of Mathematical Sciences at the University of Arkansas Cheng Li, 2014 Assistant professor at the Department of Statistics and Applied Probability, National University of Singapore Patrick Yu Zhao, 2014  Risk Strategy Advisor, Ant Financial Jiangtao Gou, 2014 Department of Mathematics and Statistics, Villanova University Jiening Martin Chen, 2014 Data Scientist, Volterra Zhenyu Zhao, 2014 Data Science Director, Tencent Yang Tang, 2014 Kenneth McCallum, 2013  Data Scientist, Amazon James Pustejovsky, 2013  School of Education, University of Wisconsin, Madison Dong Xi, 2013 Novartis, NJ Juanjuan Li, 2012 Associate Director, Alnylam Pharmaceuticals Eduardo Fonseca Mendes, 2012  School of Applied Mathematics, Fundacao Getulio Vargas, Brazil Huanhuan Wang, 2012 Reining Capital, China Elizabeth (Beth) Tipton, 2011 Associate Professor of Statistics, Department of Statistics and Data Science, Northwestern Univeristy Elaine Yi Wu, 201 Director, Daiichi Sankyo, Inc. LiLi Yao, 2011  Associate Principal Scientist, Merck Yuan Liao, 2010  Associate Professor of Economics at Rutgers University Kunyang Shi, 2010 Forest Laboratories, NJ Lingyun Liu, 2009  Director, Biostatistics, Vertex Pharmaceuticals Christopher Rhoads, 2008 NEAG School of Education, University of Connecticut Haoliang Eric Song, 2007 Senior Director, Biostatistics, Neoleukin Therapeutics Xin Wang, 2006 Senior Director, Bristol Myers Squibb Jiaxiao Shi, 2006 Kaiser Permanente Zhiping Linda Sun, 2005 Senior Director, Biostatistics, Merck Heping He, 2004 Gary Harntsbarger, 2002 Senior Scientific Fellow, Takeda Alexandre Xavier Ywata de Carvalho, 2002 Head of Econometrics, Instituto de Pesquisa Economica Aplicada, Brazil Hua Li, 2001 Shuguang Huang, 2001 Chief Scientific Officer, Stat4ward LLC Brent Logan, 2001 Department of Biostatistics, Medical College of Wisconsin Xiangyang Liu, 2000 Johnson and Johnson Shengyan Sam Hong, 1998 Executive Director, MacroGenics, Inc. Joan Z. Yu, 1998 Consumer and Market Knowledge, Procter & Gamble Jason A. Osborne, 1997 Department of Statistics, North Carolina State University Yi-Lin Chiu, 1997 Director, Statistics at AbbVie Jill R. Glassman, 1995 Biostatistician/Senior Manager Quantitative Analysis, Stanford School of Medicine Edward C. Malthouse, 1995 Integrated Marketing Communications Department, Medill School of Journalism, Northwestern University Daniel B. Hall, 1994 Department of Statistics, University of Georgia Paul Coe, 1993 Dominican University Eric D. Nordmoe, 1993 Department of Mathematics, Kalamazoo College Jiahe Qian, 1993 Educational Testing Service

Secondary Menu

• Graduate Placements

Current Career Positions of Duke Statistical Science Ph.D. Graduates

Graph shows positions of those awarded a Ph.D. between Fall 2005 and Summer 2022, and their current status was reported or made known to the department or the Graduate School.

*Other includes Public and K-12 Education.

Updated December 2022

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Career Placement

Wharton prepares you to become an academic leader. our phd graduates have gone on to excel at leading academic institutions, research centers, and enterprises around the globe..

Working with Wharton’s faculty, you are trained in the practices of rigorous research. You learn how to frame questions from a multi-disciplinary perspective through exposure to the broadest range of business knowledge. This breadth and depth of thinking yields new ideas, and scholars who break new ground in their selected area of research.

You leave Wharton ready to contribute meaningfully to your field, typically having published with your faculty mentors prior to graduation. Most Wharton doctoral graduates take positions at leading academic institutions, and many alumni continue working with their Wharton mentors and colleagues, returning to Wharton for conferences and colloquia throughout their careers.

Student Placements

Here’s a list of placements, by program and year of graduation, over the past 10 years:

Visit here for Accounting PhD placements.

Applied Economics

World bank Post doc at NYU Furman center. Treasury’s Office of Financial Research. UT Dallas National University of Singapore

Brattle Group University of Wisconsin Business,  Post Doc at Treasury Brattle Group Cornerstone Research Rutgers Business School Cornerstone Research

OECD Federal Reserve Board NYU, Postdoc and Hong Kong University Princeton, Postdoc

University of North Carolina, Chapel Hill University of Texas, Austin Bank of Canada NBER, Postdoc

Stanford University Cornerstone The Vanguard Group

Michigan State Federal Reserve Bank of New York (Post-doc at Chicago Booth) London School of Economics

Cornell University Microsoft Research NERA Economic Consulting University of Colorado, Boulder

Econ One Harvard Business School National Taiwan University Nuna Health Toulouse School of Economics University of California, Merced

Baruch College Clemson University Northwestern University Putnam Investments Research Affiliates

Consumer Financial Protection Bureau Duke University Indiana University University of Delaware University of Wisconsin, Madison

Berkeley Research Group University of Michigan U.S. Treasury Department Sungkyunkwan University, SKK GSB

Note: The Applied Economics program was created in Fall 2008 and, therefore, has placed students beginning 2013.

Ethics & Legal Studies

Visit here for Ethics & Legal Studies PhD placements. 

The Ohio State University, Fisher College of Business Vanderbilt University, Owen Graduate School of Management

BlackRock Cornerstone Research Drexel University, LeBow College of Business Harvard Business School Rothschild & Co

BlackRock Boston Consulting Group Columbia Business School Kenan-Flagler Business School of the University of North Carolina McGill University MIT Sloan Universidad Carlos III de Madrid University of Hong Kong

Capital One Stockholm School of Economics

Arizona State University Hong Kong University of Science and Technology University of Florida University of Warwick, Warwick Business School

BI Norwegian Business School INSEAD London Business School (2 placements) Peking University University of Hong Kong (2 placements)

Carnegie Mellon University Cornell University Cornerstone Research Peking University Southern Methodist University University of Wisconsin, Madison

AQR Capital Management Carnegie Mellon University, Tepper School of Business Citadel Tulane University, Freeman School of Business University of Chicago, Booth School of Business University of Southern California, Marshall School of Business

Federal Reserve Bank of New York University of Michigan University of North Carolina, Chapel Hill

Boston College Cornell University Federal Reserve Board Michigan State University Ohio State University University of Houston

Google University of California, Los Angeles University of Delaware University of Minnesota University of Oxford

Google University of Delaware

Mingshi Investment Management Peking University Southern Methodist University

Carnegie Mellon University University of British Columbia University of North Carolina, Chapel Hill University of Rochester University of Wisconsin, Madison

Cornell University Getulio Vargas Foundation Southern Methodist University U.S. Securities and Exchange Commission University of Southern California

New York University University of Florida

Cornerstone Research KAIST (Korea Advanced Institute of Science and Technology) University of Iowa University of Minnesota, Twin Cities

Aalto University School of Economics University of California, San Diego

Federal Reserve Board

Health Care Management & Economics

Charles River Associates Baylor University Cornell University Medical Campus (Weill) University of Miami USAID Emory University Securities and Exchange Commission (SEC)

Harvard Business School New York University University of Pennsylvania, Perelman School of Medicine NYU Langone Medical Center Analysis Group

University of Virginia Northwestern University, Kellogg School of Management RAND Corporation University of Pittsburgh Analysis Group

Indiana University Bloomington John Hopkins Bloomberg School of Public Health University of Pennsylvania, Perelman School of Medicine US Department of Health and Human Services

Asian Development Bank RAND Corporation

RAND Corporation

Cornell Medical School RAND Corporation Thomas Jefferson University University of Pennsylvania, Perelman School of Medicine Urban Institute

RAND-UCLA (Joint Post-Doc) San Diego State University Temple University, Fox Business School

Columbia University Peking University Urban Institute US Army Medical Department Telehealth Office

Bill and Melinda Gates Foundation Brigham and Women’s Hospital University of Pennsylvania, Perelman School of Medicine

Massachusetts General Hospital

University of Missouri University of Porto, Faculty of Economics

Bocconi University Ohio State University University of Southern California, Marshall School of Business Rice University New York University, Stern School of Business Massachusetts Institute of Technology

George Washington University University of Texas, Austin

University of Illinois at Urbana-Champaign University of North Carolina, Chapel Hill Sungkyunkwan University

Cornell University Stanford University

University of Texas, Austin University of Wisconsin, Madison

IESE Business School, Barcelona Campus University of LUISS (Rome)

INSEAD Purdue University University of North Carolina, Chapel Hill University of Pittsburgh University of South Carolina University of Texas, Austin

George Washington University University of North Carolina, Chapel Hill University of Washington, Bothell

Georgia State University Moscow School of Management, SKLOKOVO Institute for Emerging Market Studies Nanyang Business School Rutgers University

George Washington University Harvard University INSEAD University of Maryland, Smith School of Business University of Minnesota, Carlson School Washington University, St. Louis

New York University University of Hartford

Instituto De Empresa University of Michigan

Brigham Young University Florida International University National University of Singapore New York Department of Economics University of Illinois-Urbana Champaign

Visit here for Marketing PhD placements. 

Operations, Information and Decisions

Visit here for Operations, Information and Decisions PhD placements. 

University of Florida Carnegie Mellon University Columbia University Rutgers University

Massachusetts Institute of Technology The Voleon Group

University of Chicago, Booth School of Business University of California, Berkeley Emory University Rutgers University Citadel Air Liquide

INSEAD Massachusetts Institute of Technology, Sloan School of Management University of Vienna DV01

CLVmetrics IBM Stanford University

Carnegie Mellon University Columbia University Queens College Rice University Walmart Labs

Columbia University New Jersey Institute of Technology Yahoo Labs

The Climate Corporation Credit Suisse Rutgers University University of North Carolina, Chapel Hill

Krossover Intelligence Stanford University

Northwestern University US Census Bureau

Harvard University Princeton University University of Pennsylvania

London School of Economics Massachusetts Institute of Technology

Colombia University, Earth Institute (Post-Doc)

Yale University