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.
- 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
| 2024.9 - Present | Ph.D in Computer Science Dartmouth College |
| 2020.9 - 2024.6 | B.S. in Mathematics and Applied Mathematics South China University of Technology |
🏆 Selected Awards
2026
ICML 2026 Golden Reviewer.
2026
Best Student Paper Award, The 37th International Conference on Algorithmic Learning Theory.
2024
Outstanding Graduation Thesis Award.
2023
Yingli Scholarship (2/68).
2023
Hong Ping Evergreen Fund (Outstanding Research Potential).
2022
Mathematical Contest in Modeling: Finalist (0.2% of participants).
2022
First-class scholarship: top 2% of grade (2/68).
📢 News
| Date | Update |
|---|---|
| 2026.06 | 💰 Honored to receive the ISIT 2026 Travel Grant. |
| 2026.06 | 🎉 Our paper, “How Does Orthogonalization Adapt to the Neural-Network Hessian Structure? A Gradient Self Outer-Product Analysis at Initialization,” has been accepted to the ICML 2026 HILD Workshop. |
| 2026.05 | 🎙️ Gave a talk about RMNP at Dartmouth–Berkeley–Rice AI Reading Group (Recording). |
| 2026.05 | ✨ New blog: A Proof of Orthogonalized and Row-Normalized Descent Directions is now online. |
| 2026.05 | 🎉 Honored to be recognized as an ICML 2026 Golden Reviewer. Grateful for the recognition from the community. |
| 2026.05 | ✨ New blog in understanding Row normalization and orthogonalization for NN online. Welcome to discuss! |
| 2026.05 | 🎉Two paper has been accepted to ICML 2026, including RMNP ! We will soon release two blog posts to discuss the rich intuitions behind RMNP. |
| 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! |
📚 Selected Research
* indicates equal contribution.
RMNP: Row-Momentum Normalized Preconditioning for Scalable Matrix-Based Optimization
Shenyang Deng*, Zhuoli Ouyang*, Tianyu Pang, Zihang Liu, Ruochen Jin, Shuhua Yu, Yaoqing Yang
The 43rd International Conference on Machine Learning (ICML 2026)
[arxiv] [Additional Asymptotic Theory on NNs]
Shenyang Deng*, Zhuoli Ouyang*, Tianyu Pang, Zihang Liu, Ruochen Jin, Shuhua Yu, Yaoqing Yang
The 43rd International Conference on Machine Learning (ICML 2026)
[arxiv] [Additional Asymptotic Theory on NNs]
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
[arxiv] [download]
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
[arxiv] [download]
Depth, Not Data: An Analysis of Hessian Spectral Bifurcation
Shenyang Deng*, Boyao Liao*, Zhuoli Ouyang*, Tianyu Pang, Yaoqing Yang
IEEE International Symposium on Information Theory (ISIT 2026) (Extended version in preparation for IEEE Transactions on Information Theory)
[arxiv]
Shenyang Deng*, Boyao Liao*, Zhuoli Ouyang*, Tianyu Pang, Yaoqing Yang
IEEE International Symposium on Information Theory (ISIT 2026) (Extended version in preparation for IEEE Transactions on Information Theory)
[arxiv]
📎 Check out more of my work on Google Scholar
🎙️ Recent Talks
2026.05.05
RMNP
Dartmouth--Berkeley--Rice AI Reading Group. Recording
Dartmouth--Berkeley--Rice AI Reading Group. Recording
2026.02.26
Suspicious Alignment of SGD
Fields Institute. Recording
Fields Institute. Recording
2025.11.27
Suspicious Alignment of SGD
Dartmouth--Berkeley--Rice AI Reading Group. Recording
Dartmouth--Berkeley--Rice AI Reading Group. Recording
📝 Academic Service
Journal
Reviewer for TPAMI
2026
Reviewer for ICML 2026
2025
Reviewer for ICLR 2026
🍽️ 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 →