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Welcome to My Homepage!
My Name is Sungtae Lee, M.D.. I graduated from the College of Medicine, Yonsei University, Korea. I served in the military for ~ 3 years (2021.04 ~ 2024.04) as a public health doctor.
What excites me the most is "Problem Solving". Research and Business are both processes of solving problems which is why I am interested in both fields. To be specific about research, I am interested in Behavioral Science, Reinforcement Learning, Artificial Intelligence. My research interests include sample-efficient deep reinforcement learning and imitation learning.
Currently, I am preparing a business using AI.
Contact Info : mail
NEWS
2023.12 : Our paper "Unsupervised Object Interaction Learning WIth Counterfactual Dynamics Models" (co-first author) has been accepted to AAAI 2024.
2023.04 : Our paper "Massively parallel evaluation and computational prediction of the activities and specificities of 17 small Cas9s." (co-author) has been accepted to Nature Methods.
2023.03 : Our paper "Unsupervised Object Interaction Learning With Counterfactual Dynamics Models" (co-first author) has been accepted to ICLR 2023 RRL workshop (poster).
2021.05 : Our paper "Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks" (co-first author) has been accepted to ICML 2021 (short talk).
2021.02 : I graduated from the College of Medicine, Yonsei University with Dean's award in Research.
2020.10 : Our paper "Shortest-Path Constrained Reinforcement Learning for Sparse Reward Tasks" (co-first author) has been accepted to Neurips 2020 Workshop.
2020.09 : Our paper (co-author) on Prime-editor efficiency prediction has been accepted to Nature Biotechnology.
2020.07 : Our paper (co-first author) on ABE/CBE efficiency prediction has been accepted to Nature Biotechnology.
2020.06 : Our paper (second author) on Cas9 variant activity prediction has been accepted to Nature Biotechnology.
2020.01 : Our paper (second author) on xCas9, SpCas9-NG, SpCas9 high-throughput analysis has been accepted to Nature Biomedical Engineering.
2019.12-2020.02 : I will intern at Honglak Lee's Lab, University of Michigan (Prof. Honglak Lee). Topic : Sample-Efficient Deep Reinforcement Learning.
2019.11 : I will give a talk at CHORUS Seoul 2019.
Topic : Basic Neural Network & Cas9 Activity Prediction.
2019.11 : Our paper (second author) on SpCas9 activity prediction has been accepted to Science Advances.
2017.06-2021.02 : I will intern at HKim Lab, Yonsei University (Prof. HyungBum Kim). Topic : Crispr-Cas9 activity prediction via CNN.
2016.01-2016.12 : I will intern at BI Lab, SNU (Prof. ByungTak Zhang). Topic : Deep Learning, Music Classification, Reinforcement Learning - I wrote an arxiv paper.
2013.01 : I will participate in Korean Mathematical Olympiad (KMO) Winter School.
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