Changyeon Kim
changyeon.kim [AT] kaist.ac.kr
Hello. I am a PhD student at KAIST, advised by Jinwoo Shin and Kimin Lee, and a visiting PhD student at UT Austin advised by Yuke Zhu. I also worked closely with Honglak Lee at University of Michigan and Joseph J. Lim at KAIST.
My research interest lies on applying RL algorithms to challenging tasks where reward specification is burdensome. To this end, I am focusing on designing RL algorithms to tackle practical and challenging scenarios like environments without well-shaped rewards and unseen novel environments. I am also broadly interested in RL researches including RL with representation learning, language‐conditioned RL, and offline RL.
Prior to my graduate studies, I was a machine learning engineer at Recommendation Team of Kakao. Before that, I completed my BS in Computer Science at KAIST.
News
Sep 22, 2023 | ARP has been accepted to NeurIPS 2023. See you in New Orleans ! |
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Jun 19, 2023 | I will attend ICML 2023 in person for presenting workshop paper (ARP). Feel free to contact to meet or chat in Hawaii, USA . |
Jan 21, 2023 | Preference Transformer is accepted to ICLR2023 . Hope to see you in Kigali, Rwanda ! |
Publications
- Subtask-Aware Visual Reward Learning from Segmented Demonstrations2024
Work Experience
Recommendation Team, Kakao
Machine Learning Engineer (Dec 2020 ~ Feb 2022)
Data Science Group, Institute of Basic Science
Resarch Intern advised by Prof. Meeyoung Cha (Jul 2019 - Nov 2020)
Honors and Awards
Travel Award ($2,000), Conference on Neural Information Processing Systems (NeurIPS), 2023Recipient ($3,000), KAIST-Google Partnership Program, 2023
Recipient ($2,000), Google East Asia Student Travel Grant, 2023
Travel Award ($1,000), International Conference on Learning Representations (ICLR), 2023
Dean's List, KAIST Department of Engineering, 2019
Recipient ($5,000), Line Scholarship, 2019
Recipient, National Science and Engineering Scholarship, Korea Ministry of Science and ICT, 2017 - 2019
Recipient ($3,000), Kwanjeong Scholarship, 2017
Invited Talks
Guide Your Agent with Adaptive Multimodal RewardsLG AI Research (New Orleans, LA, USA)
Academic Services
Conference Reviewer: ICML (2024), NeurIPS (2024)Workshop Reviewer: Frontiers4LCD@ICML'23