About Me

I am currently a second-year PhD student at Dartmouth College. I am honored to be advised by Prof. Yaoqing Yang. Prior to this, I earned my Bachelor’s degree in Mathematics and Applied Mathematics from South China University of Technology in 2024. My primary research interests lie in learning theory 📊 and optimization 📈.


✨ Research Interests

I am interested in both classical learning theory problems (Rademacher Complexity, Covering Number, PAC-Bayesian, etc.) and recently emerging theory problems (primarily focusing on the statistical and optimization properties of large-scale deep neural networks). If you have any interesting related problems, feel free to discuss with me anytime! I am very open to cooperation.

My current research primarily focuses on:

  • Analyze the optimization properties (Non-Smoothness, Hessian, River-Valley, etc.) of large-scale neural networks, the behavior of optimization algorithms under specific loss landscapes, and develop scalable optimization algorithms based on these optimization properties and algorithms’ behavior.
  • Investigate non-vacuous and theoretically interpretable metrics for data/model statistical complexity in neural networks training, and determine how the interplay between data complexity and model complexity can lead to improved generalization and robustness performance.

📖 Education

Period Degree Institution
2024.9 – Present Ph.D in Computer Science Dartmouth College
2020.9 – 2024.6 B.S. in Mathematics & Applied Mathematics South China University of Technology

📢 News

Date Update
2026.03 🎉 Our paper about “Hessian Spectral Bifurcation” has been accepted to ISIT 2026.
2026.03 📄 New preprint about Matrix-Based Optimization: RMNP: Row-Momentum Normalized Preconditioning for Scalable Matrix-Based Optimization
2026.02 🏆 My first paper as first author, “Suspicious Alignment of SGD”, received Best Student Paper Award at the 37th International Conference on Algorithmic Learning Theory (ALT) 2026!
2026.02 🎙️ Giving a talk at Fields Institute on Feb 26th about our ALT paper (Recording)
2026.02 📄 New short paper preprint about Hessian: Depth, Not Data: An Analysis of Hessian Spectral Bifurcation)
2026.02 📝 Serving as a reviewer for ICML 2026
2025.12 🎉 “Suspicious Alignment of SGD” has been accepted to ALT 2026 .
2025.12 💰 Honored to receive a $2,000 grant from Lambda AI
2025.10 📝 Serving as a reviewer for ICLR 2026
2025.10 👋 First post on this website - welcome!

📚 Publications

Selected Research

Suspicious Alignment of SGD: A Fine-Grained Step Size Condition Analysis
Shenyang Deng, Boyao Liao, Zhuoli Ouyang, Tianyu Pang, Minhak Song, Yaoqing Yang
The 37th International Conference on Algorithmic Learning Theory (ALT), 2026
🏆 Best Student Paper Award
[Paper]
Suspicious Alignment of SGD

📎 Check out more of my work on Google Scholar


🍽️ Miscellaneous

I am a food enthusiast who loves both eating and cooking. I enjoy preparing a hearty dinner after a busy work schedule and then rewarding myself with a game of StarCraft II 🎮. Here are some photos of the dishes I have made: See Gallery →