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Rising Stars in Data Science

Celebrating the potential of exceptional data scientists through an intensive research and career workshop.

Rising Stars in Data Science | Stanford HAI

The Rising Stars in Data Science Workshop will take place November 9-10, 2026, at the University of Chicago, in collaboration with Harvard University,  the University of California San Diego, and Stanford University. The workshop focuses on celebrating and fast-tracking the careers of exceptional data scientists at a critical inflection point: the transition to a postdoctoral scholar, research scientist, industry research position, or tenure-track position. Over the past five years, the Rising Stars workshop has hosted over 180 Rising Stars from nearly 50 institutions.

The University of Chicago will host the seventh annual Rising Stars workshop to showcase the exciting, innovative data science initiatives at UChicago, Harvard, UC San Diego, and Stanford. This event will provide PhD students and postdocs the opportunity to plug into these networks, platforms, and opportunities. The workshop also aims to increase representation and diversity in data science by providing a platform and a supportive mentoring network to navigate academic careers in data science. All graduate students and postdocs, including those who belong to groups underrepresented in data science, are encouraged to apply, including but not limited to people of all racial, ethnic, geographic, and socioeconomic backgrounds, sexual orientations, genders, and persons with disabilities.

The two-day workshop will feature career and research panels, networking and mentoring opportunities, and research talks from the Rising Stars. Participants will gain insights from faculty panels on career development questions such as: how to start your academic career in data science; how to strategically sustain your career through research collaborations, publications, and skill development; and how to form meaningful interdisciplinary collaborations in data science with industry and government partners. Participants will also hear inspiring keynote talks from established, cutting-edge leaders in data science.

Eligibility & Guidelines

If you have any questions about your eligibility, please send an email to data-science@uchicago.edu.

  • Applicants must be full-time graduate students within 1 year of obtaining a PhD, or a current postdoctoral scholar, fellow, or researcher.

  • We welcome applicants from a wide variety of fields and backgrounds: any eligible PhD or postdoc who is engaging in rigorous, data-driven inquiry is encouraged to apply.

  • Applicants from all institutions, including but not limited to the University of California San Diego, the University of Chicago, Stanford University, and Harvard University, are encouraged to apply.

  • Applicants may only submit one application.

  • Applicants may have nominations from a maximum of two faculty members or advisors.

The application period is now closed for 2026.

Workshop Format

  • Rising Star research talks

  • Panels (career development, data science research)

  • Keynote address

  • 1:1 meetings with faculty members

  • Networking within the UChicago, Harvard, UC San Diego, and Stanford data science ecosystems

Shahira Abousamra
Postdoctoral Scholar, Department of Biomedical Data Science, Stanford University
Aparna Ananthasubramaniam
PhD student, Schools of Information and Social Work, University of Michigan
Anubrata Das
Postdoctoral Researcher, Department of Information, Risk, and Operations Management, McCombs School of Business, University of Texas at Austin
Andy Haupt
HAI Postdoctoral Fellow
Siyu He
Postdoctoral Scholar, Department of Biomedical Data Science, Stanford University
Soroor Hediyeh-Zadeh
PhD Student, Institute of Computational Biology, Computational Health Center, Helmholtz Munich
Nanum Jeon
PhD Candidate, Sociology, UCLA
Junsol Kim
PhD Student, Department of Sociology, University of Chicago
Benjamin Laufer
PhD Student, Cornell Tech
Alisa Liu
PhD Student, Computer Science & Engineering, University of Washington
Jiacheng Liu
PhD Candidate, Paul G. Allen School of Computer Science and Engineering, University of Washington
Xiran Liu
Postdoctoral Research Associate, Data Science Institute, Brown University
Yifan Liu
PhD Student, Carter School of Public Policy, Georgia Tech
Aishwarya Mandyam
Data Science Scholar
Patrícia Muñoz Ewald
PhD Candidate, Department of Mathematics, University of Texas at Austin
Eshaan Nichani
PhD Student, Electrical & Computer Engineering, Princeton University
Liangzu Peng
PhD Student, Electrical and Systems Engineering, University of Pennsylvania
Chao Qin
Tahseen Rabbani
Postdoctoral Scholar, Department of Computer Science, University of Chicago
Jacy Reese Anthis
PhD Student, Sociology and Econometrics & Statistics, University of Chicago
Eric Sun
Postdoc, Genetics & Biomedical Data Science, Stanford
Gokul Swamy
PhD Student, Robotics Institute, Carnegie Mellon University
Peihao Wang
PhD Candidate, Department of Electrical and Computer Engineering, University of Texas at Austin
Yixuan (Roy) Wang
PhD Student, Computing and Mathematical Science, Caltech
Nathan Waniorek
PhD Candidate, Computational and Applied Mathematics, University of Chicago
Ruihan Wu
Postdoctoral Researcher, Department of Computer Science and Engineering, University of California, San Diego
Jerry Yao-Chieh Hu
PhD Student, Computer Science, Northwestern University
Yikun Zhang
PhD Candidate, Statistics, University of Washington
Yuhui Zhang
PhD Student, Computer Science, Stanford University
Bo Zhao
PhD Student, Computer Science and Engineering, UC San Diego
Susan Clark
Physics
John Duchi
Statistics & Electrical Engineering
Laura Gwilliams
Assistant Professor of Psychology and, by courtesy, of Linguistics, Stanford University | Wu Tsai Neurosciences Institute and Stanford HAI Faculty Scholar
Sanmi Koyejo
Assistant Professor of Computer Science, Stanford University; Faculty Affiliate, Stanford HAI
Lihua Lei
Economics
Benjamin Nachman
Associate Professor of Particle Physics and Astrophysics and, by courtesy, of Physics and of Statistics
Julia Palacios
Associate Professor of Statistics and of Biomedical Data Science
Dennis Sun
Associate Professor (Teaching) of Statistics, Stanford University
Brian Trippe
Statistics
Ellen Vitercik
Assistant Professor, Management Science and Engineering and Computer Science, Stanford University
Stefan Wager
Assistant Professor of Operations, Information, and Technology
James Zou
Assistant Professor of Biomedical Data Science and, by courtesy, of Computer Science and of Electrical Engineering

Watch the 2025 Info Session

November 11:

8:30am-9:30am

Check-In and Breakfast

9:30am-9:45am 

Welcome and Opening Remarks

  • Guido Imbens

9:45am- 10:00am 

Overview: Data Science at Stanford, UCSD, & UChicago

  • Julia Palacios

  • Chris Mentzel

10:00am-11:00am

Faculty Advice: The Job Search 

  • Laura Gwilliams

  • Scott Linderman

  • Brian Trippe

  • Lily Weng

  • Moderator: Michael Franklin

11:00am-11:15am 

Break

11:15am-12:15pm

Job Talk Showcase

  • Ellen Vitercik

  • Moderator: Jason Fries

12:15pm-1:15pm

Lunch Break

1:15pm-2:15pm

Concurrent Lightning Talks

Track 1: Deep Learning Theory & Optimization (Simonyi Conference Center)

  • Presenters:

    • Patricia Munoz Ewald

    • Eshaan Nichani

    • Bo Zhao

  • Session Chair: Yu-Xiang Wang

Concurrent Lightning Talks

Track 2: AI for Biology & Biomedicine (W415 Pre-function Room)

  • Presenters:

    • Siyu He

    • Xiran Liu

    • Aishwarya Mandyam

    • Yuhui Zhang

  • Session Chair: James Zou

2:15pm-2:30pm

Break

2:30pm-3:30pm

Mentor Meetings & Drop-In Office Hours

3:30pm-4:30pm

Concurrent Lightning Talks

Track 3: Reinforcement Learning & Game Theory (Simony Conference Center)

  • Presenters:

    • Benjamin Laufer

    • Andreas Haupt

    • Chao Qin

    • Gokul Swamy

  • Session Chair: Laura Gwilliams

Concurrent Lightning Talks

Track 4: Scientific Computing & AI for Science (W415 Pre-function Room)

  • Presenters:

    • Liangzu Peng

    • Yixuan Wang

    • Nathan Waniorek

  • Session Chair: Susan Clark

4:30pm

Closing Remarks

4:35pm-6:00pm

Reception & Poster Session 


November 12:

8:30am-9:30am

Breakfast

9:30am-10:30am 

Job Talk Showcase

  • Tijana Zrnic

  • Moderator: Stuart Geiger

10:30am- 11:15am 

Mentor Meetings & Drop-In Office Hours

11:15am-11:30am

Break

11:30am-12:30pm 

Concurrent Lightning Talks

Track 5: Causal Inference, Policy & Applied ML (Simonyi Conference Center)

  • Presenters:

    • Aparna Ananthasubramaniam

    • Yikun Zhang

    • Nanum Jeon

    • Yifan Liu

  • Session Chair: Stefan Wager

Concurrent Lightning Talks

Track 6: Computer Vision & Medical Imaging (W415 Pre-function Room)

  • Presenters:

    • Peihao Wang

    • Eric Sun

    • Shahira Abousamra

  • Session Chair: Alex Cloninger

12:30pm-1:30pm

Lunch Break

1:30pm-2:30pm

Panel: Rising Stars Alumni

  • Kristina Gligoric

  • Lihua Lei

  • Katie Spoon

  • Moderator: David Uminsky

2:30pm-2:45pm

Break

2:45pm-3:45pm

Concurrent Lightning Talks

Track 7: Trustworthy, Responsible, & Interpretable AI (Simonyi Conference Center)

  • Presenters:

    • Tahseen Rabbani

    • Anubrata Das

    • Jiacheng Liu

    • Ruihan Wu

  • Session Chair: Yuxin Chen

Concurrent Lightning Talks

Track 8: Language Models, NLP & Human-AI Interaction (W145 Pre-function Room)

  • Presenters:

    • Alisa Liu

    • Junsol Kim

    • Jacy Anthis

  • Session Chair: Roxana Daneshjou

3:45pm-4:00pm

Break

4:00pm-5:00pm

Panel: Beyond the Job Offer: Making the Most of Year 1

  • Ramesh Johari

  • Molly Offer-Westort

  • Berk Ustun

  • Risa Wechsler

  • Moderator: Alex Cloninger

5:00pm-6:30pm

Closing Reception (Kali Greek Stanford)

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