Cathy Wu

My research area is AI in Transportation, which asks: How will AI change transportation science & engineering? I address the bottleneck of decision-making at scale – traditional optimization approaches are overwhelmed by the complexity of transportation systems. This affects every stakeholder; my work explores how data, compute, and inference can expand what is feasible:

• Scenario Analysis: Accelerating evaluation of emerging mobility technologies.
• Infrastructure Engineering: Modernizing infrastructure planning, design, and operations.
• Policy & Governance: Expanding capacity for policymaking and regulatory design.
• User Behavior: Decoding and anticipating end-user mobility decisions.

• Feb 2026

  Have you noticed how navigation apps include walking & waiting for public transit, but excludes parking & walking for driving? Our article on parking-aware navigation (T-ITS 2026) digs into this and is featured on the MIT home page!

• Feb 2026

  Learning to Segment for Vehicle Routing Problems was selected for an Oral (1%) presentation at ICLR 2026!

• Jan 2026

  Two papers accepted to ICLR 2026: Learning to Segment for Vehicle Routing Problems and Towards Efficient Constraint Handling in Neural Solvers for Routing Problems!

• Aug 2025

  MIT News features our work (TR-C 2025) showing that controlling vehicle speeds to mitigate traffic across a city can cut carbon emissions between 11 and 22 percent. To do this, we use deep reinforcement learning to optimize one million eco-driving scenarios.

• Apr 2025

  I’m so excited to be awarded the 2025 Ole Madsen Mentoring Award from the MIT Department of Civil and Environmental Engineering (CEE). Mentoring is a large part of what makes this job so rewarding.

• Apr 2025

  I was honored to keynote MIT’s Campus Preview Weekend (CPW) that welcomes the newly admitted undergraduate class to campus. I remember how fun my CPW was! I spoke about: What If We Could Design Societal-Scale Systems That Just Work?

• Sep 2024

  I am honored to give a Keynote at TRC-30, the 30th year anniversary conference of the Transportation Research Part C: Emerging Technologies (TR-C) journal. I spoke on Learning-guided Optimization for Mobility, focusing on how AI can facilitate the design of next-generation mobility systems.

See the Group page for lab members and alumni, or visit Prospective Members to get involved.

Representative recent papers from my research.

2. 

   Featured

   Learning to Segment for Vehicle Routing Problems

   Wenbin Ouyang, Sirui Li, Yining Ma, Cathy Wu

   International Conference on Learning Representations (ICLR) 2026 Oral (1%) (28% acceptance rate)

   Also presented at: 12th Triennial Symposium on Transportation Analysis conference (TRISTAN XII) (33% acceptance)

   neural-combinatorial-optimization

   📄 Paper 👥 Reviews
4. 

   Featured

   Learning-Guided Prioritized Planning for Lifelong Multi-Agent Path Finding in Warehouse Automation

   Han Zheng, Yining Ma, Brandon Araki, Jingkai Chen, Cathy Wu

   Journal of Artificial Intelligence Research (JAIR) 2026

   neural-combinatorial-optimization rl-and-traffic
6. 

   Featured

   Mitigating Metropolitan Carbon Emissions with Dynamic Eco-driving at Scale

   Vindula Jayawardana, Baptiste Freydt, Ao Qu, Cameron Hickert, Edgar R. Sanchez, Catherine Tang, Mark Taylor, Blaine Leonard, Cathy Wu

   Transportation Research Part C: Emerging Technologies (TR-C) 2025 MIT News Daily Feature

   rl-and-traffic empirical-rl

   📄 Paper 🌐 Project

   Media:MIT News, NewScientist, Anthropocene, The Cool Down, Brighter Side of News
8. 

   Featured

   Learning-Guided Rolling Horizon Optimization for Long-Horizon Flexible Job Shop Scheduling

   Sirui Li, Wenbin Ouyang, Yining Ma, Cathy Wu

   International Conference on Learning Representations (ICLR) 2025 MIT Home Page Feature (32% acceptance rate)

   neural-combinatorial-optimization

   📄 Paper 👥 Reviews

   Media:MIT News
10. 

    Featured

    Model-Based Transfer Learning for Contextual Reinforcement Learning

    Jung-Hoon Cho, Vindula Jayawardana, Sirui Li, Cathy Wu

    Advances in Neural Information Processing Systems (NeurIPS) 2024 (26% acceptance rate)

    empirical-rl

    📄 Paper 🌐 Project 👥 Reviews 💻 Code

    Media:MIT News, SciTech Daily, CO/AI, ScienceDaily, The Brighter Side of News
12. 

    Featured

    Reproducibility in Transportation Research: A Hands-on Tutorial

    Cathy Wu, Bidisha Ghosh, Zuduo Zheng, Irene Martínez

    IEEE International Conference on Intelligent Transportation Systems (ITSC) 2024

    benchmarks-and-tools transportation-system-modeling

    🌐 Project 💻 Code
14. 

    Featured

    Neural Neighborhood Search for Multi-agent Path Finding

    Zhongxia Yan, Cathy Wu

    International Conference on Learning Representations (ICLR) 2024 MIT Home Page Feature (31% acceptance rate)

    neural-combinatorial-optimization

    📄 Paper 👥 Reviews 💻 Code

    Media:MIT News, Sourcing Journal, The Robot Report, SciTechDaily

• 6.7920 Reinforcement Learning Fall 2024, Fall 2023, Fall 2022, Spring 2021, Spring 2020
  Previously 6.7950/6.246.
• 1.041/1.200 Transportation Spring 2024, Spring 2023, Fall 2021, Fall 2020, Fall 2019
• 6.231 Dynamic Programming and Reinforcement Learning Spring 2022
• EE290O Multi-agent reinforcement learning for autonomous traffic Fall 2018 (UC Berkeley)

• MIT CEE Ole Madsen Mentoring Award, 2025
• NSF CAREER Award, 2023 – 2028
• IEEE ITS Best Dissertation Award, First Place Award, 2019
• Microsoft Location Summit, First Place Award, Hall of Fame Inductee, 2019
• CUTC Milton Pikarsky Memorial Award, 2018
• UC Berkeley Outstanding Graduate Student Instructor Award, CS189 Machine Learning, 2018
• ACM Future of Computing Academy, Inaugural Class, 2017
• UC Berkeley ITS Outstanding Graduate Student Award, 2017
• IEEE Best Paper Award Honorable Mention, Intelligent Transportation Systems Conference (ITSC), 2016
• Rising Stars Workshop, Carnegie Mellon University, Department of Electrical and Computer Engineering (ECE), 2016
• Dwight David Eisenhower Graduate Fellowship (DDETFP), Awardee, 2015
• National Defense Science and Engineering (NDSEG) Graduate Fellowship, Awardee, 2013
• National Science Foundation (NSF) Graduate Fellowship, Fellow, 2013 – 2018
• UC Berkeley Chancellor's Fellowship for Graduate Study, 2013 – 2017

Highlighted entries indicate leadership roles or particularly impactful service contributions.