I am a third year PhD Student at The Operations Research Center at MIT, where I am fortunate to be advised by Rahul Mazumder.

Research Interests

I am interested broadly in the use of mathematical optimization methods (first/second-order methods, mixed-integer programming, robust optimization) in deep learning and high-dimensional statistics.

Papers

Reasoning Models Can Be Accurately Pruned via Chain-of-Thought Reconstruction arXiv
Ryan Lucas, Kayhan Behdin, Zhipeng Wang, Shao Tang, Qingquan Song, Rahul Mazumder

Pixie: Fast and Generalizable Supervised Learning of 3D Physics arXiv, Website
Long Le, Ryan Lucas, Chen Wang, Chuhao Chen, Dinesh Jayaraman, Eric Eaton, Lingjie Liu

Preserving Deep Representations in One-Shot Pruning: A Hessian-Free Second-Order Optimization Framework arXiv
Ryan Lucas, Rahul Mazumder
International Conference on Learning Representations (ICLR, 2025)

Certified Robust Neural Networks: Generalization and Corruption Resistance arXiv
Amine Bennouna, Ryan Lucas, Bart Van Parys
International Conference on Machine Learning (ICML, 2023)
– Runner-up of INFORMS 2023 Data Mining Best Paper Award (General Track)
– Winner of INFORMS 2023 Workshop on Data Science Best Student Paper

Holistic Robust Data-Driven Decisions arXiv
Amine Bennouna, Bart Van Parys, Ryan Lucas

Contact

Please reach out if you have an interest in my work.
ryanlu[at]mit.edu
MIT Operations Research Center