Rohan Chandra is currently a postdoctoral research fellow in Texas Robotics, advised by Dr. Joydeep Biswas and Dr. Peter Stone, at the University of Texas, Austin. Rohan obtained his B.Tech from the Delhi Technological University, New Delhi in 2016 and completed his MS and PhD in 2018 and 2022 from the University of Maryland advised by Dr. Dinesh Manocha. His doctoral thesis focused on autonomous driving in dense, heterogeneous, and unstructured traffic environments. Rohan is a Microsoft Future Leader in Robotics and AI, KAUST Rising Star in AI 2023, UMD’21 Future Faculty Fellow, RSS’22 Pioneer, and he is a recipient of the UMD’20 summer research fellowship. He has published his work in top computer vision and robotics conferences (CVPR, ICRA, IROS) and has participated in workshops and program committees of leading conferences in robotics, computer vision, artificial intelligence, and machine learning. He has also given invited talks at academic seminars and workshops and has served on robotics panels alongside distinguished faculty.
Apr 2023 Finalist for the Charles A. Caramello Distinguished Dissertation Award!
Apr 2023 Organizing the first workshop on RSS 2023 Workshop on Multi-Agent Planning and Navigation in Challenging Environments !
Mar 2023 We developed SocialGym 2 for simulating multi-agent social navigation in indoor environments!
Mar 2023 SocialMAPF will be published in RA-L and presented at IROS'23!
Feb 2023 Appointed as Associate Editor for RA-L!
Jan 2023 Selected for the 2022-2023 Microsoft Future Leaders in Robotics and AI: Celebrating Diversity and Innovation Seminar Series!
Jan 2023 METEOR accepted to ICRA'23!
Dec 2022 Selected for the Rising Stars in AI Symposium 2023 at KAUST (declined)
Oct 2022 New pre-print on arXiv on MAPF with strategic agents with private incentives! (Blue Sky short version accepted to AAAI FSS'23)
Jun 2022 BGAP and GameOpt accepted to IROS'22 and ITSC'22!
Jun 2022 Starting a postdoc at UT Austin !
Jan 2023 Selected for the 2022-2023 Microsoft Future Leaders in Robotics and AI: Celebrating Diversity and Innovation Seminar Series!
Feb 2023 Selected for the Rising Stars in AI Symposium 2023, hosted at KAUST (declined)!
Oct 2022 Selected to participate in the Global Sandpit on Trustworthy Human-Machine Teaming!
May 2022 Selected as part of the 2022 RSS Pioneers Workshop!
2020 - 2021 Selected as part of the 2020-2021 cohort (22 selected out of approximately 5, 000 doctoral students at UMD) of Future Faculty Fellows.
Summer 2020 Awarded the Summer Research Fellowship by The Graduate School, UMD.
News
Jun 2023 Publicity and Social Media Chair for the International Symposium on Multi-Robot & Multi-Agent Systems 2023!Apr 2023 Finalist for the Charles A. Caramello Distinguished Dissertation Award!
Apr 2023 Organizing the first workshop on RSS 2023 Workshop on Multi-Agent Planning and Navigation in Challenging Environments !
Mar 2023 We developed SocialGym 2 for simulating multi-agent social navigation in indoor environments!
Mar 2023 SocialMAPF will be published in RA-L and presented at IROS'23!
Feb 2023 Appointed as Associate Editor for RA-L!
Jan 2023 Selected for the 2022-2023 Microsoft Future Leaders in Robotics and AI: Celebrating Diversity and Innovation Seminar Series!
Jan 2023 METEOR accepted to ICRA'23!
Dec 2022 Selected for the Rising Stars in AI Symposium 2023 at KAUST (declined)
Oct 2022 New pre-print on arXiv on MAPF with strategic agents with private incentives! (Blue Sky short version accepted to AAAI FSS'23)
Jun 2022 BGAP and GameOpt accepted to IROS'22 and ITSC'22!
Jun 2022 Starting a postdoc at UT Austin !
Research Interests
- Multi-agent Planning and Navigation I am broadly interested in making robots navigate safely, efficiently, and with social compliance, in challenging environments that include humans. My specific research interests within this domain span decentralized planning under private incentives, physics-informed planning, planning-constrained perception.
- Autonomous Driving I am also interested in continuing to extend autonomous driving to denser, heterogeneous, and more unstructured traffic environments such as that in India.
Awards & Honors
Jan 2023 Selected for the 2022-2023 Microsoft Future Leaders in Robotics and AI: Celebrating Diversity and Innovation Seminar Series!
Feb 2023 Selected for the Rising Stars in AI Symposium 2023, hosted at KAUST (declined)!
Oct 2022 Selected to participate in the Global Sandpit on Trustworthy Human-Machine Teaming!
May 2022 Selected as part of the 2022 RSS Pioneers Workshop!
2020 - 2021 Selected as part of the 2020-2021 cohort (22 selected out of approximately 5, 000 doctoral students at UMD) of Future Faculty Fellows.
Summer 2020 Awarded the Summer Research Fellowship by The Graduate School, UMD.
Professional Activities
Apr 2023 Organizing the first workshop on RSS 2023 Workshop on Multi-Agent Planning and Navigation in Challenging Environments !
Feb 2023 Appointed as Associate Editor for RA-L!
Apr 2022 Organizing the first workshop on Behavior-driven Autonomous Driving in Unstructured Environments at IROS 2022!
Apr 2022 Invited to co-chair the Intelligent Transportation session at ICRA'22 !
January 2022 Invited speaker at the HPIV Workshop at WACV'22.
October 2021 Invited to serve on the program committee for the ICCV'21 MAIR2 Workshop.
July 2021 Invited speaker at the Perception and Control for Autonomous Navigation in Crowded, Dynamic Environments Workshop at RSS'21. Video
Publications
(Refer to google scholar for recent publications.)PhD Thesis
Towards Autonomous Driving in Dense, Heterogeneous, and Unstructured Traffic Rohan Chandra.Multi-Agent Systems and Planning
- GamePlan: Game-Theoretic Multi-Agent Planning with Human Drivers at Intersections, Roundabouts, and MergingRohan Chandra, Dinesh Manocha in ICRA/RAL'22.
- Game-Theoretic Planning for Risk-Aware Human DriversRohan Chandra, Mingyu Wang, Mac Schwager, Dinesh Manocha in ICRA'22.
- B-GAP: Behavior-Rich Simulation and Navigation for Autonomous DrivingAngelos Mavrogiannis, Rohan Chandra, Dinesh Manocha in RAL'22.
Driver Behavior Modeling
- Using Graph-Theoretic Machine Learning to Predict Human Driver Behavior Rohan Chandra, Aniket Bera, Dinesh Manocha in IEEE Transactions on Intelligent Transportation Systems, 2021.
- CMetric: A Driving Behavior Measure Using Centrality FunctionsRohan Chandra, Uttaran Bhattacharya, Trisha Mittal, Aniket Bera, Dinesh Manocha in IROS 2020.
- Graphrqi: Classifying Driver Behaviors Using Graph SpectrumsRohan Chandra, Uttaran Bhattacharya, Trisha Mittal, Xiaoyu Li, Aniket Bera, Dinesh Manocha in ICRA 2020.
Trajectory Prediction
- Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMsRohan Chandra, Tianrui Guan, Srujan Panuganti, Trisha Mittal, Uttaran Bhattacharya, Aniket Bera, Dinesh Manocha in RAL/IROS 2020.
- RobustTP: End-to-End Trajectory Prediction for Heterogeneous Road-Agents in Dense Traffic with Noisy Sensor InputsRohan Chandra, Uttaran Bhattacharya, Christian Roncal, Aniket Bera, Dinesh Manocha in ACM CSCS 2019.
- TraPHic: Trajectory Prediction in Dense and Heterogeneous Traffic Using Weighted InteractionsRohan Chandra, Uttaran Bhattacharya, Aniket Bera, Dinesh Manocha in CVPR 2019.
Tracking
- RoadTrack: Tracking Road Agents in Dense and Heterogeneous EnvironmentsRohan Chandra, Uttaran Bhattacharya, Tanmay Randhavane, Aniket Bera, Dinesh Manocha in ICRA 2020.
- DensePeds: Pedestrian Tracking in Dense Crowds Using Front-RVO and Sparse FeaturesRohan Chandra, Uttaran Bhattacharya, Aniket Bera, Dinesh Manocha in IROS 2019.