Seojin Kim
Student at Seoul National University
School of Law
osikjs [AT] snu.ac.kr
About
I received my M.S. in Artificial Intelligence, advised by Prof. Jinwoo Shin at KAIST. I received my B.S. in Chemistry (major), Computer Science (double major), and Mathmatics (double major) at KAIST.
My main research goal is to efficiently adapt large language models for domain-specific applications, e.g., drug discovery (ICML'24, NeurIPSW'24), accelerated inference (ICMLW'25), and visual image generation (Preprint'25).
At this moment, I have paused my AI research career to pursue a J.D. at School of Law in Seoul National University. While I am uncertain whether I will resume my career as an AI researcher, I at least hope to contribute to the AI community through my expertise in the legal profession.
Publications (*: Equal contribution)
FontAdapter: Instant Font Adaptation in Visual Text Generation
Myungkyu Koo, Subin Kim, Sangkyung Kwak, Jaehyun Nam, Seojin Kim, Jinwoo Shin
Preprint, 2025
Mamba Drafters for Speculative Decoding
Daewon Choi, Seunghyuk Oh, Saket Dingliwal, Jihoon Tack, Kyuyoung Kim, Woomin Song, Seojin Kim, Insoo Han, Jinwoo Shin, Aram Galstyan, Shubham Katiyar, Sravan Babu Bodapati
ICML Workshop on Efficient Systems for Foundation Models (ICMLW-ES-FoMo), 2025
Confidence-aware Denoised Fine-tuning of Off-the-shelf Models for Certified Robustness
Suhyeok Jang*, Seojin Kim*, Jinwoo Shin, Jongheon Jeong
Transactions on Machine Learning Research (TMLR), 2024
An Efficient Tokenization for Molecular Language Models
Seojin Kim, Jaehyun Nam, Jinwoo Shin
NeurIPS Workshop on AI for New Drug Modalities (NeurIPSW-AIDrugX), 2024
Data-Efficient Molecular Generation with Hierarchical Textual Inversion
Seojin Kim, Jaehyun Nam, Sihyun Yu, Younghoon Shin, Jinwoo Shin
International Conference on Machine Learning (ICML), 2024
NeurIPS Workshop on New Frontiers of AI for Drug Discovery and Development (NeurIPSW-AI4D3), 2023
Fragment-based Multi-view Molecular Contrastive Learning
Seojin Kim*, Jaehyun Nam*, Junsu Kim, Hankook Lee, Sungsoo Ahn, Jinwoo Shin
Transactions on Machine Learning Research (TMLR), 2024
ICLR Workshop on Machine Leraning for Materials (ICLRW-ML4Materials), 2023
Confidence-aware Training of Smoothed Classifiers for Certified Robustness
Jongheon Jeong*, Seojin Kim*, Jinwoo Shin
AAAI Conference on Atrificial Intelligence (AAAI), 2023
ECCV Workshop on Adversarial Robustness in the Real World (ECCVW-AROW), 2022
FontAdapter: Instant Font Adaptation in Visual Text Generation
Myungkyu Koo, Subin Kim, Sangkyung Kwak, Jaehyun Nam, Seojin Kim, Jinwoo Shin
Mamba Drafters for Speculative Decoding
Daewon Choi, Seunghyuk Oh, Saket Dingliwal, Jihoon Tack, Kyuyoung Kim, Woomin Song, Seojin Kim, Insoo Han, Jinwoo Shin, Aram Galstyan, Shubham Katiyar, Sravan Babu Bodapati
Confidence-aware Denoised Fine-tuning of Off-the-shelf Models for Certified Robustness
Suhyeok Jang*, Seojin Kim*, Jinwoo Shin, Jongheon Jeong
Data-Efficient Molecular Generation with Hierarchical Textual Inversion
Seojin Kim, Jaehyun Nam, Sihyun Yu, Younghoon Shin, Jinwoo Shin
Fragment-based Multi-view Molecular Contrastive Learning
Seojin Kim*, Jaehyun Nam*, Junsu Kim, Hankook Lee, Sungsoo Ahn, Jinwoo Shin
Confidence-aware Training of Smoothed Classifiers for Certified Robustness
Jongheon Jeong*, Seojin Kim*, Jinwoo Shin
Education
Seoul National UniversityMar. 2025 - Present
J.D. in School of Law
Korea Advanced Institute of Science and Technology (KAIST)Sep. 2021 - Feb. 2025
M.S. in Artificial Intelligence (completed Ph.D. coursework without completing a dissertation)
Korea Advanced Institute of Science and Technology (KAIST)Mar. 2016 - Aug. 2021
B.S. in Chemistry (major), Computer Science (double major), and Mathematics (double major)
Ranked 1st Overall in the Department (GPA:4.08/4.3, major GPA: 4.24/4.3)