Jiaxin Song

I am a PhD student at the University of Illinois Urbana-Champaign, advised by Prof. Bhaskar Ray Chaudhury. I work on computational economics and algorithmic game theory, with a side interest in program synthesis.

Previously, I received my bachelor’s degree in computer science from Shanghai Jiao Tong University in 2023, where I worked with Prof. Biaoshuai Tao on algorithmic game theory and Prof. Qinxiang Cao on formal methods. In summer 2024, I worked with Prof. Yu Feng on program synthesis.

You can reach me at jiaxins8@illinois.edu.

News

Sep 2026
I’m joining Amazon as an Applied Scientist Intern in the Automated Reasoning group in San Jose, working on verification of IAM refinement.
Aug 2026
I visited MIT this summer, working with Prof. Manish Raghavan and Prof. Kate Donahue.
May 2026
Our data pricing paper was selected for an ICML 2026 oral presentation, and our online chores paper was accepted at EC 2026.

Research

(α–β) indicates alphabetical author order. Other author lists follow contribution order.

Under submission

Revenue-Optimal Pricing for Budget-Constrained Buyers in Data Markets

(α–β) Bhaskar Ray Chaudhury, Jugal Garg, Eklavya Sharma, Jiaxin Song

Paper

EC 2026

Online MMS Allocation for Chores

(α–β) Jiaxin Song, Biaoshuai Tao, Wenqian Wang, Yuhao Zhang

Paper

Summary

The general lower bound exactly matches the trivial n-MMS guarantee. Better bounds are possible when the number or range of distinct disutilities is limited.

ICML 2026Spotlight + oral

Equilibrium Pricing in Oligopolistic Data Markets

(α–β) Bhaskar Ray Chaudhury, Jugal Garg, Eklavya Sharma, Jiaxin Song

Paper

Summary

Exact Nash equilibria may fail to exist. The paper establishes a pricing profile where switching to a uniform price cannot improve any seller’s revenue by more than a factor of two.

WWW 2026

Data Pricing via Competitive Equilibrium

(α–β) Bhaskar Ray Chaudhury, Jugal Garg, Aniket Murhekar, Jiaxin Song

Paper

AAMAS 2026

Fair Revenue Compensation in Data Markets

Nathan Joe Joseph, Jiaxin Song, Bhaskar Ray Chaudhury

Paper

EC 2025

Approximability Landscape of Welfare Maximization within Fair Allocations

(α–β) Xiaolin Bu, Zihao Li, Shengxin Liu, Jiaxin Song, Biaoshuai Tao

Paper

NeurIPS 2025

On the Existence and Complexity of Core-Stable Data Exchanges

Jiaxin Song, Pooja Kulkarni, Parnian Shahkar, Bhaskar Ray Chaudhury

Paper

Summary

Concave payoffs and convex costs guarantee existence, but computing a core-stable exchange is PPAD-hard. A pivoting approach performs well in the paper’s experiments.

ICML 2025

You Get What You Give: Reciprocally Fair Federated Learning

Aniket Murhekar, Jiaxin Song, Parnian Shahkar, Bhaskar Ray Chaudhury, Ruta Mehta

Paper Code

Summary

Under the paper’s assumptions, the mechanism admits Nash equilibria and aligns agents’ payoffs with their contributions. The analysis and experiments also examine improvements in accuracy, welfare, and data sharing.

EAAMO 2025