Sirui Li

Sirui Li

PhD student at MIT
LIDS, IDSS, IDPS

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. During my PhD, I’ve spent time at Microsoft Research, Amazon AWS and MathWorks as an intern. 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.

Articles in Review

  • 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.


  • Towards Foundation Models for Mixed Integer Linear Programming
    Sirui Li, Janardhan Kulkarni, Ishai Menache, Cathy Wu, Beibin Li
    The Thirteenth International Conference on Learning Representations (ICLR), 2025. To Appear.
    ( preprint )
  • Learning-Guided Rolling Horizon Optimization for Flexible Job Shop Scheduling
    Sirui Li, Wenbin Ouyang, Yining Ma, and Cathy Wu
    The Thirteenth International Conference on Learning Representations (ICLR), 2025. To Appear.
    ( paper coming soon )
  • Hybrid System Stability Analysis of Multi-Lane Mixed-Autonomy Traffic
    Sirui Li, Roy Dong, and Cathy Wu
    IEEE Transactions on Robotics (T-RO), 2024.
    ( paper / preprint )
  • Model-Based Transfer Learning for Contextual Reinforcement Learning
    Jung-Hoon Cho, Vindula Jayawardana, Sirui Li, Cathy Wu
    The 38th Conference on Neural Information Processing Systems (NeurIPS), 2024.
    ( paper / preprint / website / MIT News )
  • 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.
    ( paper / preprint / website )
  • 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.
    ( paper / preprint )
  • Learning to Configure Separators in Branch-and-Cut
    Sirui Li*, Wenbin Ouyang*, Max B. Paulus, and Cathy Wu
    The 37th Conference on Neural Information Processing Systems (NeurIPS), 2023.
    ( paper / preprint / website / MIT News [Home Page Feature] )
  • 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.
    ( paper / preprint )
  • Cooperation for Scalable Supervision of Autonomy in Mixed Traffic
    Cameron Hickert, Sirui Li, and Cathy Wu
    IEEE Transactions on Robotics (T-RO), 2023.
    ( paper / preprint / MIT News )
  • The Impact of Task Underspecification in Evaluating Deep Reinforcement Learning
    Vindula Jayawardana, Catherine Tang, Sirui Li, Dajiang Suo, Cathy Wu
    The 36th Conference on Neural Information Processing Systems (NeurIPS), 2022.
    ( paper / preprint / website )
  • Learning to delegate for large-scale vehicle routing
    Sirui Li*, Zhongxia Yan*, Cathy Wu
    The 35th Conference on Neural Information Processing Systems (NeurIPS), 2021. [Spotlight < 3%]
    ( paper / preprint / website / MIT News )
  • Conditional Linear Regression
    Diego Calderon*, Brendan Juba*, Sirui Li*, Zongyi Li*, and Lisa Ruan*.
    International Conference on Artificial Intelligence and Statistics (AISTATS), 2020.
    ( paper / preprint )
  • 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.
    ( paper )

Last Updated on 01/22/2025