Seungchan Kim


I am a second-year PhD student in the Robotics Institute at Carnegie Mellon University, advised by Sebastian Scherer. My research interests are at the intersection of robotics, computer vision, and reinforcement learning.

Previously, I received B.S. in Applied Mathematics & Computer Science and M.S. in Computer Science from Brown University. During my time at Brown, I worked with George Konidaris and Michael Littman, focusing on research in deep reinforcement learning.

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Using Computational Analysis of Behavior to Discover Developmental Change in Memory-Guided Attention Mechanisms in Childhood
Dima Amso, Lakshmi Govindarajan, Pankaj Gupta, Diego Placido, Heidi Baumgartner, Andrew Lynn, Kelley Gunther, Tarun Sharma, Vijay Veerabadran, Kalpit Thakkar, Seungchan Kim, Thomas Serre
PsyArXiv Preprint
Combating the Compounding-Error Problem with a Multi-step Model
Kavosh Asadi, Dipendra Misra, Seungchan Kim, Michael Littman
arXiv preprint. CoRR abs/1905.13320 [cs.LG]
DeepMellow: Removing the Need for a Target Network in Deep Q-Learning
Seungchan Kim, Kavosh Asadi, Michael Littman, George Konidaris
Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI 2019)
The 4th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2019)
project page / code
Removing the Target Network from Deep Q-Networks with the Mellowmax Operator
Seungchan Kim, Kavosh Asadi, Michael Littman, George Konidaris
Proceedings of the 18th International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2019)
CSCI1430 Computer Vision, Brown University
Teaching Assistant, Spring 2019

CSCI0040 Intro to Scientific Computing and Problem Solving, Brown University
Teaching Assistant, Spring 2015
Conference Reviewer: ICML 2020, AAAI 2021, ICLR 2021, NeurIPS 2021
Workshop Reviewer:
- NeurIPS 2019 Workshop on ML for Health, Workshop on ML and Physical Sciences
- NeurIPS 2020 Workshop on the Challenges of Real-World Reinforcement Learning

Website Template from Jon Barron.