Students

Recs

Ethos

At UT Austin, we train students to become full-stack researchers—and increasingly, designers of the systems that do research. Our students learn to carry projects end-to-end: from idea generation and theory to data creation, analysis, and iterative refinement across diverse subfields. Using modern AI (including agentic workflows) and scalable computation, students build reproducible pipelines that can ingest and update planetary-scale data—like satellite imagery and other high-dimensional sources. But the goal isn’t tool use for its own sake: students learn to set the objectives, constraints, and evaluation standards that guide these systems through large spaces of hypotheses, while grounding results in causal inference and careful measurement. The outcome is scholarship that can rigorously test policy counterfactuals and translate evidence into durable, responsible improvements in societal well-being.

We welcome students at every stage to engage with projects—from motivated high-schoolers to undergraduates, graduate students, and those from highly non-traditional backgrounds. Across advising, committee service, co-authorship, internships, and research-group membership, this network now includes more than 40 students. See also [Jobs] and [Student Awards].

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Graduate Students (Co-)Advised

Doctoral

SayedMorteza Malaekeh, PhD in Sustainable Systems Engineering, UT Austin (2026-present)

Andrés Cruz, Ph.D. in Government, UT Austin (2024-present)

Nicolas Audinet de Pieuchon, Ph.D. in Data Science and AI, Chalmers University of Technology, Sweden (2024-present)

Kazuki Sakamoto, Ph.D. in Analytical Sociology, Linköping University, Sweden (2024-present)

Ritwik Vashistha, Ph.D. in Statistics and Data Science, UT Austin (2024-present)

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Master’s

Hamza Aziz Khan, Master’s Student of Computational Science, Uppsala University, Sweden (Ongoing)

Mishu Dhar, Master’s Student of Computational Social Science, Linköping University, Sweden (Ongoing)

Cem Mert Dallı, Master’s Student of Applied Data Science, University of Gothenburg, Sweden (Ongoing)

Johannes Fagerlind, Master’s Student of Computational Social Science, Linköping University, Sweden (Defended 2026)

  • Thesis: Horizontal Inequality, Income Shocks & Civil Conflict: Using High-Resolution Spatial Wealth Estimates and Causal Inference Methods to Investigate Patterns of Civil Violence in Africa [PDF] [Data] [.bib] [>]

Mattias Antar, Master’s Student of Computational Social Science, Linköping University, Sweden (Defended 2026)

Mikael P. Gustafsson, Master’s Student of Computational Social Science, Linköping University, Sweden (Defended 2024)

  • Thesis: Estimating Aid Effectiveness in Fragile and Conflict-affected States: Evidence from Satellite-based Inference in Somalia [PDF] [.bib] [>]

Cindy Conlin, Master’s Student of Computational Social Science, Linköping University, Sweden (Defended 2024)

  • Thesis: Using Machine Learning and Daytime Satellite Imagery to Estimate Aid’s Effect on Wealth: Comparing China and World Bank Programs in Africa [PDF] [Data] [Code] [.bib] [>]

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External Committee Member for Graduate Students

Doctoral

Entejar Alam, Ph.D. Student in Statistics & Data Science, UT Austin (Expected 2026)

Angela Ting, Ph.D. in Statistics & Data Science, UT Austin (Defended 2025)

  • Thesis: Bayesian Nonparametric Methods for Heterogeneous Treatment and Mediation Effect Estimation
  • Role (as of 2025): Senior Biostatistician at Kenvue (formerly the consumer healthcare division of Johnson & Johnson)

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Student Co-authors (Selected)

Samuel G. Balter, Undergraduate, UT Austin

Priyanshi Chandra, Ph.D. student in the Faculty of Informatics, Università della Svizzera Italiana (Switzerland)

Cindy Conlin, Master’s Student of Computational Social Science, Linköping University (Sweden)

Eric Fan, Undergraduate, Yale

Beniamino Green, Ph.D. student in Statistics and Political Science, Yale

Rishi Hazra, Undergraduate, Department of Statistics, Harvard College

Aniket Kamat, Undergraduate, UC Berkeley, soon to be a JD student at Harvard Law School

SayedMorteza Malaekeh, Ph.D. student in Engineering, UT Austin

Markus Pettersson, Ph.D. student in Data Science and AI, Chalmers University of Technology (Sweden)

Nicolas Audinet de Pieuchon, Ph.D. student in Data Science and AI, Chalmers University of Technology (Sweden)

Kazuki Sakamoto, Ph.D. student in Analytical Sociology, Linköping University (Sweden)

Omatharv Vaidya, Ph.D. student in the Department of Computer Science, UT Austin

  • Joint work: Queryable LoRA: Instruction-Regularized Routing Over Shared Low-Rank Update Atoms [.bib]

Ritwik Vashistha, Ph.D. student in the Department of Statistics and Data Science, UT Austin

Fucheng Warren Zhu, Undergraduate, Harvard

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Plan II Honors Students

Evan Zirui Wang (AY 2025-2026)

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Undergraduate Research Assistants

Samuel G. Balter, Undergraduate, UT Austin (2026)

Yashodhara Nalawade, Undergraduate, UT Austin (2026)

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Undergraduate Interns

Ethany Castillo (Spring 2025)

Carlos Durazo (Spring 2025)

Bryan Simmons (Spring 2025)

Norah de Zwart (Fall 2024)

Genevie Sung (Fall 2024)

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Members of Research Group (Past & Present)

[More information] [Thanks]
[Link for members] [Expression of interest form]

Andrés Cruz

Peter Dunphy

Berk Filcan

Krishna Hariprasad (Boren Awardee; Fulbright UK Summer Institute Awardee)

Erica Yunyi Huang

Nivedita (Nivy) Jhunjhunwala

Siyun Jiang (now an Assistant Professor at IE University [as of 2025])

Eric (Young Seok) Kim

Dean Peng-Ting Kuo

Huimin Li

Jenna Salzman

Miranda Sullivan

Kyle Trojahn (NSF GRF Awardee, now a research analyst at E3 Alliance)

Daisy Ward

Joel Yew

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Teaching Fellows

Andrés Cruz (2023)

Gauthier Fally (2026)

Siyun Jiang (2022)

Yuning Liu (2024)

Ruofan Ma (2024)

Matthew Martin (2022)

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Student Projects

The students I’ve had the fortune to work with in various capacities are incredibly talented. Below, you can find links to some of their projects:

[6 Years a Statistician] (by Ritwik Vashistha)

[All 2024 US Political Candidates & Staff] (by Will Schrepferman)

[Local Wealth Trajectories Webpage] (by Mattias Antar)

[Methods Camp Website] (by Andrés Cruz & Matthew Martin)

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Working Together

If you have any questions, are interested in collaborating, or are interested in pursuing graduate studies at UT Austin, you can email connor.jerzak@austin.utexas.edu.

Prospective Student Form

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Resources

[How to Apply for and Get Compute Grants (for Students)]

[How to Ask Questions]

[How to Do Research]

[How to Give a Job Talk]

[How to Learn Machine Learning]

[How to Not Fool Yourself]

[How to Read a Paper]

[How to Solve Problems]

[How to Survive a PhD]

[How to Win a Best Paper Award]

[How to Write a Paper]

[How to Write an ML Paper]

[How to Run Computational Experiments]

[Learn Optimization & Training Dynamics]

[On Narrative in Writing]

[On Teams]

[Patrick Winston’s How to Speak]

[Principles of Learning Fast]

[Style: Lessons in Clarity and Grace]

[Teaching in an AI World]

[Terence Tao Teaches Mathematical Thinking]

[Tips for Early Stage Researchers]

[You and Your Research]

See syllabi in [Courses] for information about office hours. See [Awards] for information about student award winners.

See [Recommendations] for more information about letter of recommendation logistics.

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