About Me
I am a final year PhD student in Social and Engineering Systems (SES) and Statistics at Massachusetts Institute of Technology (MIT), advised by Prof. Cathy Wu. I am affiliated with MIT Laboratory for Information & Decision Systems (LIDS), Institute of Data, Systems and Society (IDSS), and MIT Statistics & Data Science Center (IDPS). I am fortunate to be supported by the Amazon Robotics Fellowship and the Michael Hammer Fellowship. I’ve spent time at Microsoft Research, Amazon AWS and MathWorks as an intern during my PhD. Prior to MIT, I received my bachelor’s degrees in Computer Science and Mathematics from Washington University in St. Louis in 2019.
My research interest broadly lies in the intersection between machine learning, operations research, and transportation. I have developed learning-guided algorithms to speed up combinatorial optimization solvers for efficient large-scale optimization. I am also interested in control theory analysis and reinforcement learning for mixed-autonomy transportation systems.
I'm on job market 2024-2025, and I am open to industry research / engineering jobs. Feel free to contact me if you know a position for which I may be a fit.
Articles in Review
-
Towards Foundation Models for Mixed Integer Linear Programming
Sirui Li, Janardhan Kulkarni, Ishai Menache, Cathy Wu, Beibin Li
- Learning-Guided Rolling Horizon Optimization for Flexible Job Shop Scheduling
Sirui Li, Wenbin Ouyang, Yining Ma, and Cathy Wu
- Temporal Transfer Learning for Traffic Optimization with Coarse-Grained Advisory Autonomy
Jung-Hoon Cho, Sirui Li, Jeongyun Kim, and Cathy Wu
Publications
Sort By: Date | Topic. Please see Google Scholar for the full list of publications.
- Hybrid System Stability Analysis of Multi-Lane Mixed-Autonomy Traffic
Sirui Li, Roy Dong, and Cathy Wu
IEEE Transactions on Robotics (T-RO), 2024. To Appear. - Model-Based Transfer Learning for Contextual Reinforcement Learning
Jung-Hoon Cho, Vindula Jayawardana, Sirui Li, Cathy Wu
38th Conference on Neural Information Processing Systems (NeurIPS), 2024. To Appear. - Generalizing Eco-Lagrangian Control via Multi-residual Task Learning
Vindula Jayawardana, Sirui Li, Cathy Wu, Yashar Farid, Kentaro Oguchi
IEEE International Conference on Robotics and Automation (ICRA), 2024. - Multi-Agent Reinforcement Learning for Assessing False-Data Injection Attacks on Transportation Networks
Taha Eghtesad, Sirui Li, Yevgeniy Vorobeychik and Aron Laszka
The 23rd International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS), 2024.
- Learning to Separate in Branch-and-Cut
Sirui Li*, Wenbin Ouyang*, Max B. Paulus, and Cathy Wu
37th Conference on Neural Information Processing Systems (NeurIPS), 2023. [MIT News Front Page] - Integrated Analysis of Human-compatible Control for Traffic Flow Stability
Sirui Li, Roy Dong, and Cathy Wu
IEEE Transactions on Control of Network Systems (TCNS), 2023. - Cooperation for Scalable Supervision of Autonomy in Mixed Traffic
Cameron Hickert, Sirui Li, and Cathy Wu
IEEE Transactions on Robotics (T-RO), 2023.
- The Impact of Task Underspecification in Evaluating Deep Reinforcement Learning
Vindula Jayawardana, Catherine Tang, Sirui Li, Dajiang Suo, Cathy Wu
36th Conference on Neural Information Processing Systems (NeurIPS), 2022.
- Learning to delegate for large-scale vehicle routing
Sirui Li*, Zhongxia Yan*, Cathy Wu
35th Conference on Neural Information Processing Systems (NeurIPS), 2021. [Spotlight < 3%]
- Conditional Linear Regression
Diego Calderon*, Brendan Juba*, Sirui Li*, Zongyi Li*, and Lisa Ruan*.
International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.
- The Congressional Classification Challenge: Domain Specificity and Partisan Intensity
Hao Yan, Sanmay Das, Allen Lavoie, Sirui Li, and Betsy Sinclair
ACM Conference on Economics and Computation (EC), 2019.
Last Updated on 10/01/2024