I am a second-year Ph.D. student at MIT Chemistry, co-advised by Tommi Jaakkola and Regina Barzilay .
My research interest includes generative models for Science, especially for bio/organic chemistry and clinical applications. Current focus is on enzymatric reactions and enzyme design.
Previously, I received my double major B.S. in Chemistry with Computer Science and Engineering at Seoul National University. I studied about Clinical time series imputation with Changhee Lee , AI-guided drug discovery at AIGENDRUG. Also, I experienced wide and deep research in Enzyme chemistry under Seokhee Kim, Organic synthesis under Dongwhan Lee, and Prebiotic peptide synthesis with Matthew Powner.
Most recent publications on Google Scholar.
‡ indicates equal contribution.
Conditional Information Bottleneck Approach for Time Series Imputation
MinGyu Choi, Changhee Lee
ICLR24: International Conference on Learning Representations
Clinical Time Series Imputation using Conditional Information Bottleneck
MinGyu Choi, Changhee Lee
NeurIPS23 DGM4H (Deep Generative Models for Health) Workshop
Triangular Contrastive Learning on Molecular Graphs
MinGyu Choi, Wonseok Shin, Yijingxiu Lu, and Sun Kim
MoML23: Molecular Machine Learning Conference
Genome mining reveals high topological diversity of ω-ester-containing peptides and divergent evolution of ATP-grasp macrocyclases
Hyunbin Lee, MinGyu Choi, Jung-Un Park, Heejin Roh, and Seokhee Kim
JACS20: Journal of the American Chemical Society
Conditional Information Bottleneck Approach for Time Series Imputation
MinGyu Choi, Changhee Lee
ICLR24: International Conference on Learning Representations
Clinical Time Series Imputation using Conditional Information Bottleneck
MinGyu Choi, Changhee Lee
NeurIPS23 DGM4H (Deep Generative Models for Health) Workshop
On Modeling and Utilizing Chemical Compound Information with Deep Learning Technologies: A Task-oriented Approach
Sangsoo Lim, Sangseon Lee, Yinhua Piao, MinGyu Choi, Dongmin Bang, Jeonghyeon Gu, and Sun Kim
CSBJ22: Computational and Structural Biotechnology Journal 2022
Triangular Contrastive Learning on Molecular Graphs
MinGyu Choi, Wonseok Shin, Yijingxiu Lu, and Sun Kim
MoML23: Molecular Machine Learning Conference
Genome mining reveals high topological diversity of ω-ester-containing peptides and divergent evolution of ATP-grasp macrocyclases
Hyunbin Lee, MinGyu Choi, Jung-Un Park, Heejin Roh, and Seokhee Kim
JACS20: Journal of the American Chemical Society
Full Resume in PDF.