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Vindula Jayawardana

Email: vindula [AT] mit [DOT] edu

I am a PhD student in computer science at MIT. I am fortunate to be advised by Prof. Cathy Wu in the Laboratory for Information and Decision Systems (LIDS). Earlier, I completed my bachelors at University of Moratuwa in Sri Lanka.

Before graduate school, I was a part of Mobility, Algorithms, and Society Lab at Cornell University and Data Science, Engineering & Analytics Research Hub of University of Moratuwa. I have also spent time at Toyota, WSO2, PickMe, and Trancite24.

I am broadly interested in learning-enabled autonomy. In light of this, I am interested in making multi-agent reinforcement learning seamlessly generalize across problem variations (solving Contextual MDPs). Real-world application-wise, I am interested in planning for autonomous vehicles with problem variations. In the past, I have also worked on mathematical programming for combinatorial optimizations and natural language processing for information extraction. Currently, I am also leading the project Greenwave.

I am always open for new collaborations. Feel free to reach out if you're interested in connecting!

Project Highlights: : AI-driven Eco-driving for Tackling Climate Change

Google Scholar  |  CV  |  LinkedIn  |  Github  |  Blog

Recent Updates
Articles in Review
  • Mitigating Metropolitan Vehicular Carbon Emissions with Semi-autonomous Vehicles using Deep Reinforcement Learning
    Vindula Jayawardana, Baptiste Freydt, Ao Qu, Cameron Hickert, Edgar Sanchez, Catherine Tang, Sunera Chandrasiri, Mark Taylor, Blaine Leonard, C. Wu
Selected Recent Publications

  • For a complete list of publications, please visit my Google Scholar page.
  • Generalizing Eco-Lagrangian Control via Multi-residual Task Learning
    Vindula Jayawardana, Sirui Li, Cathy Wu, Yashar Farid, Kentaro Oguchi

    International Conference on Robotics and Automation (ICRA), 2024

    Generalization in Planning workshop at NeurIPS 2023

    Machine Learning for Autonomous Driving Symposium, 2023

    [Paper] [Cite]
    The Impact of Task Underspecification in Evaluating Deep Reinforcement Learning
    Vindula Jayawardana, Catherine Tang, Sirui Li, Dajiang Suo, Cathy Wu

    Advances in Neural Information Processing Systems (NeurIPS), 2022

    [Website] [Paper] [Cite]
    Learning Eco-Driving Strategies at Signalized Intersections
    Vindula Jayawardana, Cathy Wu

    European Control Conference (ECC), 2022

    International Conference on Robotics and Automation (ICRA) 2022. Robotics for Climate Change workshop, 2022

    (Spotlight Talk)

    Press: On the road to cleaner, greener, and faster driving – MIT News

    Home page feature.

    Press: Perceptron: Risky teleoperation, Rocket League simulation and zoologist multiplication – Tech Crunch.
    Podcast: The Loh Down on Science Podcast - NPR.
    [Website] [Paper] [ICRA Presentation] [ICRA Poster] [ECC Video] [Cite]
    Model-free Learning of Corridor Clearance: A Near-term Deployment Perspective
    Dajiang Suo*, Vindula Jayawardana*, Cathy Wu (* equal contribution)

    IEEE Transactions on Intelligent Transportation Systems (T-ITS), 2024

    [Paper] [Cite]
    Multi-behavior Learning for Socially Compatible Autonomous Driving
    Sanjula Jayawardana, Vindula Jayawardana*, Keneeka Vidanage, Cathy Wu* (* = equal supervision)

    IEEE Intelligent Transportation Systems Conference (ITSC), 2023, to appear


    The Braess Paradox in Dynamic Traffic
    Dingyi Zhuang*, Yuzhu Huang*, Vindula Jayawardana, Jinhua Zhao, Dajiang Suo, Cathy Wu

    IEEE Intelligent Transportation Systems Conference (ITSC), 2022

    [Paper] [Cite]

    Mixed Autonomous Supervision in Traffic Signal Control
    Vindula Jayawardana, Anna Landler, Cathy Wu

    IEEE Intelligent Transportation Systems Conference (ITSC), 2021

    [Paper] [Cite]

    Fleet management for ride-pooling with meeting points at scale: a case study in the five boroughs of New York City
    Motahare Mounesan, Vindula Jayawardana, Yaocheng Wu, Samitha Samaranayake, Huy T. Vo
    To appear, 2021
    [Paper] [Cite]

    • 1.041/1.200/11.544: Transportation Systems Modeling: Teaching Assistant, MIT, Fall 2020/2021.

    • CS4622: Machine Learning: Teaching Assistant, UoM, Spring 2019.

    • CS2022: Data Structures and Algorithms: Instructor, UoM, Spring 2019.

    • CS3042: Database Systems: Teaching Assistant, UoM, Fall 2018.

    • CS2052: Computer Architecture: Teaching Assistant, UoM, Fall 2018.

    • CS2062: Object Oriented Software Development: Teaching Assistant, UoM, Spring 2018.

    • CS3962: Research and Report Writing : Teaching Assistant, UoM, Spring 2018.
    Selected Awards
    • Harold L. Hazen Teaching Award 2022, EECS MIT

    • Digital Mobility Solutions Lanka Fellowship 2018, University of Moratuwa

    • Migara Ranathunga Trust Award 2018 : National Awards for University Undergraduates in Sri Lanka

    • Gold Award at National Best Quality ICT Awards 2017 : Best ICT student technology project of the year

    • Global Finalist in NASA International Space Apps 2017
    Students Mentored
    Open Source Systems
      Massachusetts Institute of Technology
      Laboratory for Information and Decision Systems
      77 Massachusetts Avenue, 45-611
      Cambridge, MA 02139
      vindula [AT] mit [DOT] edu

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    Last Updated on 01/29/2024