Aerospace Controls Laboratory

Dong-Ki Kim


CV  /  Website  /  Google Scholar
dkkim93 [at] mit [dot] edu


  • 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

Research Interests

  • 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.