dematsunaga [at] ai [dot] kaist [dot] ac [dot] kr
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Daiki E. Matsunaga
Daiki E. Matsunaga
I am a PhD student at the Artificial Intelligence and Probabilistic Reasoning Lab (AIPR Lab) at KAIST Graduate School of AI, where I am very fortunate to be advised by Professor Kee-Eung Kim.
I am generally interested in better understanding intelligence from the perspective of agent incentives and multi-agent interactions which drive complex social behaviors. To do this, I primarily conduct fundamental research in Multi-Agent Reinforcement Learning (MARL), which is a standard mathematical formulation for sequential multi-agent decision-making under uncertainty.
Education
Education
2020. 09 - Current: MS-PhD, Graduate School of AI, KAIST, Seoul, South Korea (Advisor: Kee-Eung Kim)
2012. 09 - 2016. 09: BA, School of Political Science and Economics, Waseda University, Tokyo, Japan
Experience
Experience
2019. 04 - 2020. 08: Data Scientist at IBM Japan, Tokyo, Japan
2017. 04 - 2019. 03: IT Specialist/Consultant at IBM Japan, Tokyo, Japan
Publications (Conference)
Publications (Conference)
* indicates equal contribution
[C3] GDPO: Learning to Align Language Models with Diversity Using GFlowNets
[Paper] [Code]
Oh Joon Kwon, Daiki E. Matsunaga, Kee-Eung Kim.
EMNLP 2024
[C2] Stitching Sub-Trajectories with Conditional Diffusion Model for Goal-Conditioned Offline RL
[Paper] [Video] [Code]
Sungyoon Kim, Yunseon Choi, Daiki E. Matsunaga, Kee-Eung Kim.
AAAI 2024
[C1] AlberDICE: Addressing Out-Of-Distribution Joint Actions in Offline Multi-Agent RL via Alternating Stationary Distribution Correction Estimation
[OpenReview] [Paper] [Video] [Code]
Daiki E. Matsunaga*, Jongmin Lee*, Jaeseok Yoon, Stefanos Leonardos, Pieter Abbeel, Kee-Eung Kim.
NeurIPS 2023
Publications (Workshops)
Publications (Workshops)
* indicates equal contribution
[W1] Exploring Graph Neural Networks for Stock Market Predictions with Rolling Window Analysis
[Paper]
Daiki Matsunaga*, Toyotaro Suzumura*, and Toshihiro Takahashi
NeurIPS 2019 Workshop on Robust AI in Financial Services
Reviewer
Reviewer
NeurIPS 2022, 2023, 2024, 2025
ICML 2023, 2025
ICLR 2023, 2024, 2025, 2026
AAMAS 2023
ACML 2024
Teaching
Teaching
(AI503) Mathematics for Artificial Intelligence, TA at KAIST (2022 Fall)
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