|   | Diyang Li 李笛扬[Email] [Google Scholar] [LinkedIn] | 
I am a third-year Ph.D. student in the Department of Computer Science at Cornell University, where I am fortunate to be advised by Prof. Kyra Gan.
My research interests are in the intersection of statistical machine learning and optimization. 
I received my bachelor degree from Nanjing University of Information Science & Technology in 2023.
During my undergrad, I was a visiting student in the Machine Learning Department at Mohamed bin Zayed University of AI.
Research
- Targeted Maximum Likelihood Learning: An Optimization Perspective 
 Diyang Li, Kyra Gan
 Thirty-Ninth Conference on Neural Information Processing Systems (NeurIPS 2025)
- Generalized Fast Exact Conformalization 
 Diyang Li
 Thirty-Eighth Conference on Neural Information Processing Systems (NeurIPS 2024)
- Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s) 
 Diyang Li, Charles Ling, Zhiqiang Xu, Huan Xiong, Bin Gu
 Twelfth International Conference on Learning Representations (ICLR 2024), Spotlight
- When Online Learning Meets ODE: Learning without Forgetting on Variable Feature Space 
 Diyang Li, Bin Gu
 Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI 2023)
- GAGA: Deciphering Age-path of Generalized Self-paced Regularizer 
 Xingyu Qu*, Diyang Li*, Xiaohan Zhao, Bin Gu
 Thirty-Sixth Conference on Neural Information Processing Systems (NeurIPS 2022), Spotlight
- Chunk Dynamic Updating for Group Lasso with ODEs 
 Diyang Li, Bin Gu
 Thirty-Sixth AAAI Conference on Artificial Intelligence (AAAI 2022)
Program Committee
- International Conference on Machine Learning (ICML): 2022, 2024, 2025
- Neural Information Processing Systems (NeurIPS): 2023, 2024, 2025
- International Conference on Learning Representations (ICLR): 2024, 2025, 2026
- International Conference on Artificial Intelligence and Statistics (AISTATS): 2023, 2024, 2025, 2026
- AAAI Conference on Artificial Intelligence (AAAI): 2023, 2024, 2025, 2026
- NeurIPS Workshop on Optimization for Machine Learning (OPT-ML): 2023, 2024, 2025

