Chutong Yang

I am a third-year Ph.D. student in Computer Science at the University of Texas at Austin, where I am fortunate to be advised by Kevin Tian. I have a broad interest in the design and analysis of algorithms in theoretical computer science with particular interests including but not limited to learning theory, differential privacy, algorithmic fairness, and optimization. I recently gain more interest on AI for math, i.e. multiagents for math research. My work has received generous funding from the Amazon AI PhD fellowship.

In 2023, I received my Master's in Computer Science degree from Stanford University, where I was fortunate to work with Omer Reingold and Aaron Sidford. I was also fortunate to work closely with Lunjia Hu. In 2020, I received my B.S. double major in Computer Science and Mathematics from the University of California, San Diego, and worked with Max Hopkins.

(Check Google Scholar for a full list of publications. The authors are in alphabetical order if no * mentioned.)

Simultaneous Blackwell Approachability and Applications to Multiclass Omniprediction
Lunjia Hu, Kevin Tian, Chutong Yang
COLT, 2026

Spherical Leech Quantization for Visual Tokenization and Generation
Yue Zhao*, Hanwen Jiang, Zhenlin Xu, Chutong Yang, Ehsan Adeli, Philipp Krähenbühl,
CVPR(Highlight), 2026

Proportionality from Low-Dimensional Approval Data
Zhiyi Huang, Gregory Kehne, Chutong Yang
In Submission, 2026
Also presented at AAMAS for extended abstract, 2026 Also presented at EC workshop: New Directions in Social Choice, 2025

Private Geometric Median in Nearly-Linear Time
Syamantak Kumar, Daogao Liu, Kevin Tian, Chutong Yang
NeurIPS, 2025
Also presented at TPDP workshop, 2025

Omnipredicting Single-Index Models with Multi-Index Models
Lunjia Hu, Kevin Tian, Chutong Yang
STOC, 2025

Testing Calibration in Nearly-Linear Time
Lunjia Hu, Arun Jambulapati, Kevin Tian, Chutong Yang
NeurIPS, 2024

Omnipredictors for Constrained Optimization
Lunjia Hu, Inbal Livni-Navon, Omer Reingold, Chutong Yang
ICML, 2023

Active Learning Polynomial Threshold Functions
Omri Ben-Eliezer, Max Hopkins, Chutong Yang, Hantao Yu
NeurIPS, 2022

University of Texas, Austin
Ph.D. in Computer Science
Aug '23 - Now

Teaching Experience:

Worked as the Teaching Assistant for CS 395T: Continuous Algorithms
Worked as the Teaching Assistant for CS 353: Theory of Computation

Stanford University
Master of Science in Computer Science
Sep '21 - Jun '23

Research:

Research Assistantships from Professor Omer Reingold and Professor Aaron Sidford

Teaching Experience:

Worked as the Course Assistant for CS 161: Design and Analysis of Algorithms
Worked as the Course Assistant for CS 109: Introduction to Probability for Computer Scientists

University of California, San Diego
Bachelor of Science in Computer Science and Mathematics
Sep '16 - Jun '20

Awards:

Graduated from UCSD with Magna Cum Laude and as a Honor CS student

Teaching Experience:

Worked as the Teaching Assistant three times for CSE 101: Design and Analysis of Algorithms

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