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.

CV | Email | Twitter | Google Scholar | Github


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Publications
(*: equal contribution)
OGBench: Benchmarking Offline Goal-Conditioned RL
Unsupervised-to-Online Reinforcement Learning
Is Value Learning Really the Main Bottleneck in Offline RL?
Seohong Park, Kevin Frans, Sergey Levine, Aviral Kumar
NeurIPS 2024
ICML 2024 ARLET Workshop (Oral)
paper | thread | talk (10 min) | blog post
Foundation Policies with Hilbert Representations
Unsupervised Zero-Shot Reinforcement Learning via Functional Reward Encodings
METRA: Scalable Unsupervised RL with Metric-Aware Abstraction
HIQL: Offline Goal-Conditioned RL with Latent States as Actions
Controllability-Aware Unsupervised Skill Discovery
Predictable MDP Abstraction for Unsupervised Model-Based RL
Constrained GPI for Zero-Shot Transfer in Reinforcement Learning
Lipschitz-constrained Unsupervised Skill Discovery
Time Discretization-Invariant Safe Action Repetition for Policy Gradient Methods
Unsupervised Skill Discovery with Bottleneck Option Learning
Education

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

Work Experience

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

Honors and Awards

Scholarships

KFAS Overseas PhD Scholarship (Aug 2022 - Present)

Korea Foundation for Advanced Studies (KFAS)
Full tuition, insurance, and living expenses support for graduate studies

Berkeley Fellowship (Aug 2022 - Aug 2023)

Presidential Science Scholarship (Mar 2014 - Aug 2022)

Korea Student Aid Foundation (KOSAF)
Full tuition and living expenses support for undergraduate studies

Awards

Gold Prize (1st Place in Signal Processing), Samsung Humantech Paper Award (Jan 2022)

Programming Contests (Selected)

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

Services

Reviews

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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