- Ph.D. in Aeronautics and Astronautics, MIT, 2020 - current
- M.S. in Aeronautics and Astronautics, MIT, 2020
- B.S. in Electrical and Computer Engineering, Cornell University, 2016
| - Multi-Agent Reinforcement Learning
- Meta-learning
- Robot perception
| - Kwanjeong Education Foundation Scholarship, 2017
|  | Efficient Learning of Neural Network Policies via Imitation Learning and Tube MPC
Andrea Tagliabue, Dong-Ki Kim, Michael Everett, 2022
Use a Robust Tube variant of MPC to efficiently learn Neural Network policies via Imitation Learning. |  | Sharing in Multiagent Reinforcement Learning
Samir Wadhwania, Dong-Ki Kim, Shayegan Omidshafiei, 2019
Sharing information during learning in multiagent environments can reduce the need for each agent to explore the entire state space, leading to reduced learning time. |  | Learning to Teach in Cooperative MARL
Dong-Ki Kim, Shayegan Omidshafiei, 2018
Our algorithm, Learning to Coordinate and Teach Reinforcement (LeCTR), addresses peer-to-peer teaching in cooperative multiagent reinforcement learning. |  | Crossmodal Attentive Skill Learner
Shayegan Omidshafiei, Dong-Ki Kim, 2018
This work introduces the crossmodal learning paradigm and addresses the problem of learning in a high-dimensional domain with multiple sensory inputs. | |
