About me

I am a PhD Candidate in Industrial Engineering at the University of Wisconsin-Madison, under the guidance of Prof. Stephen Wright. I also hold an M.S. in Computer Science from the University of Wisconsin-Madison. Prior to my time in Madison, I earned a B.S. in Mathematics from the University of Science and Technology of China (USTC).

My research is centered on the design and analysis of optimization algorithms for machine learning applications.

I am actively seeking machine learning engineer/scientist, or quantative researcher positions in the industry!

Check out my CV here.

Contact

Email: ustcgcy [at] gmail

Publications

Changyu Gao, Andrew Lowy, Xingyu Zhou, Stephen J. Wright. Optimal Rates for Robust Stochastic Convex Optimization.   To appear in the 6th annual Symposium on Foundations of Responsible Computing (FORC 2025) [link]

Changyu Gao, Andrew Lowy, Xingyu Zhou, Stephen J. Wright. Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses.   ICML 2024. [Poster Award, Midwest Machine Learning Symposium 2024] [link]

Changyu Gao and Stephen J. Wright. Differentially Private Optimization for Smooth Nonconvex ERM.   arXiv preprint arXiv:2302.04972 (2023) [TPDP 2023 Poster] [link]

Charles Andrew Dickens, Changyu Gao, Connor Pryor, Stephen J. Wright, Lise Getoor. Convex and Bilevel Optimization for Neuro-Symbolic Inference and Learning.   ICML 2024. [link]

Dickens, Charles, Connor Pryor, Changyu Gao, Alon Albalak, Eriq Augustine, William Wang, Stephen Wright, and Lise Getoor. A mathematical framework, a taxonomy of modeling paradigms, and a suite of learning techniques for neural-symbolic systems.   ArXiv preprint arXiv:2407.09693 (2024) [link]