Seohong Park
[Pronunciation: "suh-hong" ("Seo" as in "Seoul")]
Hey! I'm a Ph.D. student at UC Berkeley advised by Sergey Levine.
I'm broadly interested in developing better reinforcement learning (RL) algorithms and understanding their mathematical properties.
I believe RL can be maximally effective and scalable when we can leverage large-scale unsupervised pre-training, potentially from unlabeled data.
To this end, I'm working on unsupervised RL, goal-conditioned RL, and offline RL.
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Github
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Publications (*: equal contribution)
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OGBench: Benchmarking Offline Goal-Conditioned RL
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Unsupervised-to-Online Reinforcement Learning
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Is Value Learning Really the Main Bottleneck in Offline RL?
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Foundation Policies with Hilbert Representations
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Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings
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METRA: Scalable Unsupervised RL with Metric-Aware Abstraction
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HIQL: Offline Goal-Conditioned RL with Latent States as Actions
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Controllability-Aware Unsupervised Skill Discovery
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Predictable MDP Abstraction for Unsupervised Model-Based RL
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Constrained GPI for Zero-Shot Transfer in Reinforcement Learning
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Lipschitz-constrained Unsupervised Skill Discovery
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Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods
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Unsupervised Skill Discovery with Bottleneck Option Learning
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University of California, Berkeley
(Aug 2022 - Present)
Ph.D. student in Computer Science
Seoul National University
(Mar 2014 - Aug 2022)
B.S. in Computer Science and Engineering
Leave of absence for military service: Sep 2017 - Sep 2020 (3 years)
The University of Tokyo
(Sep 2016 - Feb 2017)
Exchange student
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Devsisters
(Sep 2018 - Sep 2020)
Machine Learning Engineer Worked as part of the mandatory military service in the
Republic of Korea
Ace Project
(Sep 2017 - Aug 2018)
Software Engineer Worked as part of the mandatory military service in the Republic of
Korea
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Scholarships
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KFAS Overseas PhD Scholarship (Aug 2022 - Present)
Korea Foundation for Advanced Studies (KFAS)
Full tuition, insurance, and living expenses support for graduate studies
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Berkeley Fellowship (Aug 2022 - Aug 2023)
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Presidential Science Scholarship (Mar 2014 - Aug 2022)
Korea Student Aid Foundation (KOSAF)
Full tuition and living expenses support for undergraduate studies
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Awards
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Gold Prize (1st Place in Signal Processing), Samsung Humantech Paper Award (Jan 2022)
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Programming Contests (Selected)
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2nd Place, ACM-ICPC Asia Daejeon Regional Contest (Nov 2016)
1st Place, Google Code Jam Round 1C (May 2016)
3rd Place, ACM-ICPC Asia Daejeon Regional Contest (Nov 2015)
1st Place, ACM-ICPC Asia Daejeon Regional Preliminary Contest (Oct 2015)
1st Place, Korea Olympiad in Informatics (KOI) (Jul 2012)
Codeforces: polequoll
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Reviews
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Conferences:
ICML (2023, 2024),
NeurIPS (2023, 2024),
ICLR (2023, 2024, 2025),
IROS (2024)
Workshops:
ICML Frontiers4LCD (2023),
NeurIPS FMDM (2023),
ICML ARLET (2024)
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