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Gaon An Hello! I'm a final-year PhD student in computer science at Seoul National University, advised by Hyun Oh Song. Also, I lead the machine learning research team at DeepMetrics, where we build VentPilot, an AI system for ventilator management in the ICU. Previously, I received my Bachelor's degree in Economics from Seoul National University. My research interests include preference-based reinforcement learning, offline reinforcement learning, robustness, and discrete optimization. I'm particularly passionate about translating theoretical advancements into practical solutions, especially in areas like healthcare and quantitative finance. Email / CV / Google Scholar / GitHub |
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Research |
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Development and Validation of VentPilot: An AI-based Recommendation System for Mechanical Ventilation
Hong Yeul Lee*, Gaon An*, Yeonwoo Jeong, Edward J. Schenck, Ho Geol Ryu, Brian W. Pickering, Vitaly Herasevich, Daniel A. Diedrich, Seungyong Moon, Hyun-Lim Yang, Hyung-Chul Lee, Wun Hur, Jaewon Choi, Seokjun Lee, Jeongjae Lee, Won-Seok Hur, Sebin Kim, Yoonshik Kim, Rajesh Ranganath, Kyunghyun Cho, Sang-Min Lee†, Hyun Oh Song† Journal of Intensive Care, 2026 bibtex |
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Direct Preference-based Policy Optimization without Reward Modeling
Gaon An*, Junhyeok Lee*, Xingdong Zuo, Norio Kosaka, Kyung-Min Kim, Hyun Oh Song NeurIPS, 2023 paper / code / bibtex |
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Optimal channel selection with discrete QCQP
Yeonwoo Jeong*, Deokjae Lee*, Gaon An, Changyong Son, Hyun Oh Song AISTATS, 2022 paper / code / bibtex |
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Preemptive Image Robustification for Protecting Users against Man-in-the-Middle Adversarial Attacks
Seungyong Moon*, Gaon An*, Hyun Oh Song AAAI, 2022 paper / code / bibtex |
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Uncertainty-Based Offline Reinforcement Learning with Diversified Q-Ensemble
Gaon An*, Seungyong Moon*, Jang-Hyun Kim, Hyun Oh Song NeurIPS, 2021 paper / code / bibtex |
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Parsimonious Black-Box Adversarial Attacks via Efficient Combinatorial Optimization
Seungyong Moon*, Gaon An*, Hyun Oh Song ICML, 2019 (Long talk, 159/3424=4.6%) paper / code / bibtex |
Miscellanea |
Academic Service |
Reviewer, ICLR (2022-)
Reviewer, NeurIPS (2021-) Reviewer, ICML (2021-) Program Chair Committee, NeurIPS Workshop on ImageNet Past, Present, Future (2021) |
Teaching |
Teaching Assistant, Engineering Mathematics 2 (Spring 2020)
Teaching Assistant, Introduction to Deep Learning (Spring 2019, Spring 2022) |
Experience |
Head of Research, DeepMetrics (2022-)
Research Intern, Optimization and Financial engineering lab, SNU (2017-2018) |
Competitive Coding |
7th place, ARC Prize 2024 (Team name: GOA) |
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