Vindula Jayawardana

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!

CV  |  Google Scholar  |  LinkedIn  |  Github  |  Blog

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News
Apr 2024 Honored to be selected as a Rising Star in Cyber-Physical Systems research.
Apr 2024 I gave a talk at MIT CEE Graduate Student Seminar Series.
Mar 2024 I am co-organizing AVAS: Autonomous Vehicles Across Scales workshop in RSS 2024 in Delft, Netherlands.
Feb 2024 Our paper "Generalizing Cooperative Eco-driving via Multi-residual Task Learning" was accepted at ICRA. See you in Japan!
Jan 2024 Honored to receive the IEEE ITSS WiE/YP Workshop and Annual Forum Fellowship.
Dec 2023 Our paper "Model-free Learning of Corridor Clearance: A Near-term Deployment Perspective" was accepted at T-ITS.
Nov 2023 I gave a talk at LIDS Climate Tea Talks.
Oct 2023 Our paper "Robust Driving Across Scenarios via Multi-residual Task Learning" was accepted at Generalization in Planning workshop at NeurIPS 2023 and Machine Learning for Autonomous Driving Symposium.
Sep 2023 My interview with ADAS & Autonomous Vehicle International magazine is featured in the September issue.
Jul 2023 Our paper "Multi-behavior Learning for Socially Compatible Autonomous Driving" was accepted at ITSC 2023.
Jun 2023 I gave a talk at Toyota R&D in Mountain View.
Jun 2023 I am interning at Toyota in Mountain View this summer.
Dec 2022 "The Impact of Task Underspecification in Evaluating Deep Reinforcement Learning" was accepted at NeurIPS 2022 .
Dec 2022 Our paper "Learning Surrogates for Diverse Emission Models" was accepted at Climate Change AI at NeurIPS 2022.
Apr 2022 Our recent work has been featured in National Public Radio (NPR) in The Loh Down on Science Podcast.
Jun 2022 I am excited to receive 2022 Harold L. Hazen Teaching Award from EECS MIT.
Jun 2022 Our paper "The Braess Paradox in Dynamic Traffic" was accepted at ITSC 2022.
May 2022 Our recent work on eco-driving was featured as a spotlight on MIT front page.
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Research

For a complete list of publications, please visit my Google Scholar page.

Reinforcement Learning

Learning for Control

Combinatorial Optimizations

Intelligent Transportation Systems

Natural Language Processing


Generalizing Cooperative Eco-driving 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
project page | arXiv | poster | slides | video |
Learning-Augmented Vehicle Dispatching with Slack Times for High-Capacity Ride-Pooling
Youngseo Kim, Vindula Jayawardana, Samitha Samaranayake
In review 2024
arXiv |
Model-free Learning of Corridor Clearance: A Near-term Deployment Perspective
Dajiang Suo*, Vindula Jayawardana*, Cathy Wu (* equal contribution)
IEEE Transactions on IntelligentTransportation Systems (T-ITS) 2024
arXiv |
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
project page | arXiv | video | poster | slides |
Learning Eco-Driving Strategies at Signalized Intersections (MIT Homepage Spotlight)
Vindula Jayawardana, Cathy Wu,
European Control Conference (ECC) 2022
Robotics for Climate Change at ICRA 2022
project page | arXiv | video | poster | slides |

Media: MIT News | Tech Crunch | NPR |
Multi-behavior Learning for Socially Compatible Autonomous Driving
Sanjula Jayawardana, Vindula Jayawardana*, Kaneeka Vidanage, Cathy Wu* (* equal supervision)
IEEE Intelligent Transportation Systems Conference (ITSC) 2023
paper | poster |
The Braess Paradox in Dynamic Traffic
Dingyi Zhuang*, Yushu Huang*, Vindula Jayawardana, Jinhua Zhao, Dajiang Suo, Cathy Wu
IEEE Intelligent Transportation Systems Conference (ITSC) 2022
arXiv |
Mixed Autonomous Supervision in Traffic Signal Control
Vindula Jayawardana, Anna Landler, Cathy Wu
IEEE Intelligent Transportation Systems Conference (ITSC) 2021
paper |
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
arXiv | code |
Word Vector Embeddings and Domain Specific Semantic-based Semi-supervised Ontology Instance Population
Vindula Jayawardana, Dimuthu Kariyawasam, Nisansa de Silva, Shehan Perera Keet Sugathadasa, Buddhi Ayesha, Madhavi Perera
International Journal on Advances in ICT for Emerging Regions 2017
Seventeenth International Conference on Advances in ICT for Emerging Regions 2017
paper |
Deriving a Representative Vector for Ontology Classes with Instance Word Vector Embeddings
Vindula Jayawardana, Dimuthu Kariyawasam, Nisansa de Silva, Shehan Perera Keet Sugathadasa, Buddhi Ayesha,
Seventh International Conference on Innovative Computing Technology (INTECH) 2017
paper |
Legal Document Retrieval using Document Vector Embeddings and Deep Learning
Keet Sugathadasa, Buddhi Ayesha, Nisansa de Silva, Shehan Perera Vindula Jayawardana, Dimuthu Kariyawasam, Madhavi Perera
Computing Conference 2017
arXiv |
Synergistic Union of Word2vec and Lexicon for Domain Specific Semantic Similarity
Keet Sugathadasa, Buddhi Ayesha, Nisansa de Silva, Shehan Perera Vindula Jayawardana, Dimuthu Kariyawasam, Madhavi Perera
IEEE International Conference on Industrial and Information Systems (ICIIS) 2017
paper |
Selected Open Source Contributions
Charon: SCIM 2.0 Open Source Implementation (111 stars, 159 folks on Github) - Main contributor
SCIM 2.0 Compliance Test Suite (24 stars, 19 folks on Github) - Main contributor
Open Ridepool Simulator - Co-main contributor
Selected Awards
Rising Star in Cyber-Physical Systems research (University of Virginia)
IEEE ITSS WiE/YP Fellowship 2024 (IEEE Intelligent Transportation Systems Society)
Harold L. Hazen Teaching Award 2022 (EECS MIT)
Digital Mobility Solutions Lanka Fellowship 2018 (University of Moratuwa)
Migara Ranathunga Trust Award 2018 (Insititute of Engineers Sri Lanka)
Gold Award at National Best Quality ICT Awards 2017 (Sri Lanka Sector of British Computer Society)
Global Finalist in NASA International Space Apps 2017 (NASA)
Silver Medal at Junior Science Olympiad Sri Lanka 2010 (Sri Lankan Junior Science Olympiad)
Service
Workshop Organizer AVAS (RSS)
Conference Reviewer NeurIPS, ICML, AAAI, ICRA, TRB, MERCon
Journal Reviewer T-RO, T-IST, Physica A
Workshop Reviewer CCAI (NeurIPS), WMLMDS (AAAI), R2HCAI (AAAI)
Students Mentored
Graduate Students Jessica Ding (MIT - M.Eng Student 2024), Baptiste Freydt (ETH Zurich - MS Student 2022)
Undergraduate Students Sanjula Jayawardana (University of Westminster 2023), Catherine Tang (MIT-UROP 2022), Anirudh Valiveru (MIT-UROP 2022), Jiaxin He (Vanderbilt University 2022), Sunera Chandrasiri (University of Moratuwa 2022), Ammar Fayad (MIT-UROP 2021), Anna Landler (MIT-SuperUROP 2021)
Teaching
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.

Template adapted from 1 and 2.