PhD students
- Qiao Gu: 3D computer vision, robot learning
- Wei-Cheng Tseng: visual foundation models, robot learning
- Sepehr Samavi: safe control, crowd navigation. co-supervised by Angela Schoellig
- Quentin Clark: generative models, reinforcement learning
- Hossein Goli: generative models, reinforcement learning, optimization
- Yuchi (Allan) Zhao: robot manipulation, chemistry lab automation. co-supervised by Alan Aspuru-Guzik and Animesh Garg
- Yuanliang (Avery) Ju: robot manipulation, 3D vision
- Brandon (Dun-Ming) Huang: reinforcement learning, long-horizon planning, human-robot interaction, cognitive science
- Daniel Hocevar: computer vision, chemistry lab automation. co-supervised by Milica Radisic
- James Ross: computer vision, adversarial simulation generation
- Zhengyang Liang: computer vision, generative models
- Yoonsu Kang: computer vision, robot learning
Visiting students
- Alina Böhm: world models for manipulation. visiting from TU Darmstadt
undergraduate students
- Emma Xing: non-rigid body manipulation, physics simulation for robotics, imitation learning
- Yubo Wang: field robotics, navigation, localization, autonomous surface vessels
- Liyu (Laura) Tao: robot manipulation, chemistry lab automation, imitation learning
- Frank Jiang: non-rigid body manipulation, robot learning
- Nikhil Thiyagarajan: crowd navigation, multi-robot planning
- Joshua Choi: offline RL, imitation learning, data curation
- Leo Wang: robot manipulation
- Kirill Utyashev: reinforcement learning, robot learning
- Sheena Qin: vision language action models
- Natasha Yang: computer vision, robot learning, robot manipulation
- Emily Yan: computer vision, machine learning, biomedical systems
alumni: postdocs
- Qi Chen: statistical learning theory, transfer learning, meta-learning next: Assistant Professor, ML Group, Aalto University & ELLIS
- Kourosh Darvish: robotics, control, task and motion planning, machine learning, chemistry lab automation. co-supervised by Animesh Garg. next: Research Scientist, Acceleraction Consortium
alumni: graduate students
- Nathan de Lara: reinforcement learning, optimal control, optimization. next: CMU MLD PhD
- Homanga Bharadhwaj: reinforcement learning, safe exploration, robotics, recommender systems. co-supervised by Animesh Garg. next: CMU CS PhD
- Philip Huang: continual learning, field robotics, task and motion planning. co-supervised by Tim Barfoot. next: CMU CS PhD
- Andrei Ivanovic: trajectory prediction and planning. co-supervised by Igor Gilitschenski. next: Amazon Robotics
- Kevin Xie: reinforcement learning, control, 3D vision. co-supervised by Sanja Fidler. next: Research Scientist, Nvidia
- Salar Hosseini: computer vision, adversarial scenario generation. next: Samsung AI
- Ke Dong: control theory, mobile manipulation. next: Research Scientist, Tencent AI
- Yewon Lee: task and motion planning next: U. of Washington CS PhD
- Yasasa Abeysirigoonawardena: adversarial scenario generation, neural rendering. next: Research Scientist, Waabi
- Jinbang Huang: task and motion planning, control theory, optimization. co-supervised by Jonathan Kelly. next: Huawei AI, Toronto
- Anthony Lem: human pose detection and prediction. next: Epson, Toronto
- Skylar Hao: sim-to-real transfer, safe learning, statistics, machine learning
- Mohamed Khodeir: learning to plan, task and motion planning. next: Robotics Engineer, Waabi
- Blerim Abdullai: computer vision, field robotics, stochastic planning next: Robotics Engineer, Zeon Systems
alumni: research associates & visitors
- Sehee Kweon: computer vision, generative models, robot learning. visitor: Seoul National University
- Sebastian Aegidius: robot perception, motion and path planning, RL next: PhD student, UTIAS
- Derek Tan: test-time adaptation, multimodal visual search. next: PhD student, National University of Singapore
- Melissa Mozifian: visiting phd student, McGill/MILA. combining imitation and reinforcement learning. visitor: MILA, McGill
- Fabian Damken: learning planning heuristics next: Mathematics PhD student, U. Twente
alumni: undergraduate students
- Sofia Luo: computer vision, robot learning. next: UofT PhD, Toronto Computational Imaging Group
- Tanmay Patel: non-rigid body manipulation, imitation learning. next: MIT EECS PhD
- Andrew Magnuson: robot learning, manipulation. next: CMU MSR
- Ruiting Chen: physics simulation for robotic tasks, adversarial scenarios generation, mesh optimization next: Stanford CS MSc
- Alex Alexiev: non-rigid body manipulation next: MIT MechEng PhD
- Andrew Zou Li: task and motion planning, chemistry lab automation next: MSc student, CMU
- Maria Chzhen: perception, implicit occupancy and flow representation.
- Julia Chae: LiDAR and RGB representation learning next: MIT EECS PhD
- Ben Agro: learning to plan, task and motion planning, manipulation. next: UofT CS PhD / Waabi
- Yijie Wang: constrained motion planning, chemistry lab automation
- Garvish Bhutani: robotic crowd navigation
- Hamza Dugmag: field robotics, autonomous boat
- Haozhe Sheng: next: Google
- Jisu Qian: system identification
- Cathlyn Chen: backwards reachability for nonlinear systems next: UofT Neuroscience MSc
- Kathy Zhuang: computer vision for transparent objects. next: Berkeley CS MSc
- Artur Kuramshin: field robotics, autonomous boat next: MILA MSc
- Ruiqi Wang: adversarial scenario generation. next: Stanford CS MSc
- Jerry Zhu: bayesian optimisation, deep learning next: U. of Chicago Stats PhD
- Charlotte Zhang: field robotics, autonomous boat next: SFU CS PhD
- Jason Tang: continual image classification. next: UofT CS MSc
- Pranit Chawla: LiDAR and RGB representation for imitation learning. next: CMU CS MSc
- Cong Wei: video summarization, generative models next: Waterloo CS PhD
- Kamran Ramji: combining imitation and reinforcement learning. next: Apple
- Stephen Zhao: multi-agent reinforcement learning. co-supervised by Yang Xu. next: UofT CS MSc
- Dhruv Sharma: autonomous driving, robotics, computer vision. next: Huawei AI, Toronto
- Sherry Chen: video representation learning. next: UTIAS MSc
- Sally Chen: differentiable rendering for self-driving simulators. next: CMU CS MSc
- Chris Agia: 3d vision for autonomous driving. next: Stanford CS PhD
- Ali Kuwajerwala: backwards reachability for nonlinear systems. next: MILA MSc
- Jason Liu: reinforcement learning, control, simulation, and manipulation. next: CMU RI PhD
- Shichen Lu: control and reinforcement learning for mobile manipulation. next: UTIAS MSc
- Siyun Li: adversarial examples for self-driving simulators. next: Stanford CS MSc
- Yuchen Wu: combining imitation and reinforcement learning. next: UTIAS MSc
- Zidong Weng: out-of-distribution detection for image and lidar data. next: Intel
- Zihan Wang: imitation learning for robotics. next: Stanford CS MSc
- Sirui (Ariel) Chen: pedestrian trajectory prediction. next: Stanford MSc
- Kelly Zhu: trajectory prediction, uncertainty-aware planning next: UofT CS MSc
- Aditya Saigal: continual reinforcement learning next: Tenstorrent