Junhyeok Jeon | Domain-First AI Architect

About Me

I started at the intersection of biology and AI during my PhD, where I learned that the hardest part of applied AI isn't the model — it's understanding the domain deeply enough to ask the right question.

At HITS, I put that belief into practice. I led the bio-domain research behind HyperLab, an AI-powered drug discovery platform, and owned OmicsHorizon — Korea's first commercially deployed AI agent for biological data analysis. From research to architecture to product launch, I experienced the full lifecycle of turning deep science into a shipping product.

Now I'm bringing that same approach to semiconductor manufacturing — applying AI agents and data-driven methods to optimize processes at scale. The domain changes; the mindset doesn't. I treat AI not as a hammer looking for nails, but as a lens to rethink how complex physical systems are understood and operated.

I'm most energized when I can go end-to-end — from asking the right question, to building the solution, to shipping it.

Experience

2026.03 - Present

SK Hynix Research

R&D Process Engineer, NAND C&C

Applying AI-native approaches to semiconductor process development and optimization.

2024.09 - 2026.02

HITS

AI Researcher

Led bio-AI research for HyperLab, a drug discovery platform; built and shipped OmicsHorizon — Korea's first commercial AI agent for biological data analysis.

OmicsHorizon Project Lead

Korea's first commercial Bio AI Agent platform

Hyperlab

AI Drug Discovery Platform

Education

2021.03 - 2024.08

Ph.D., Chemical and Biomolecular Engineering

Systems Biology and Medicine Lab

2018.09 - 2021.02

M.S., Chemical and Biomolecular Engineering

Systems Biology and Medicine Lab

2013.02 - 2018.08

B.S., Chemical and Biomolecular Engineering

Publications

Peer-reviewed Journals

Predicting the physiological effects of multiple drugs using electronic health record

Jeon, J.^*, Hong, E.^*, Kim, J. Y., Lee, S. & Kim, H. U.

Computers in Biology and Medicine, 184: 109485 (2025)

^*co-first authors

Proteomic analysis for the effects of non-saponin fraction with rich polysaccharide from Korean Red Ginseng on Alzheimer's disease in a mouse model

Kim, S.^*, Nam, Y.^*, Kim, M. J.^*, Kwon, S. H.^*, Jeon, J.^*, Shin, S. J., ... & Moon, M.

Journal of Ginseng Research, 47(2), 302-310 (2023)

^*co-first authors

Recent development of machine learning models for the prediction of drug-drug interactions

Hong, E., Jeon, J., & Kim, H. U.

Korean Journal of Chemical Engineering, 40(2), 276-285 (2023)

Predicting biochemical and physiological effects of natural products from molecular structures using machine learning

Jeon, J.^*, Kang, S.^*, & Kim, H. U.

Natural Product Reports, 38(11), 1954-1966 (2021)

^*co-first authors

Setup of a scientific computing environment for computational biology: Simulation of a genome-scale metabolic model of Escherichia coli as an example

Jeon, J., & Kim, H. U.

Journal of Microbiology, 58, 227-234 (2020)

International Conferences

MoAgent: A Hypothesis-Driven Multi-Agent Framework for Drug Mechanism of Action Discovery

Kim, J. H., Moon, S., Kim, S., Jeon, J., Kim, T., Seo, J., ... & Kim, W. Y.

NeurIPS 2025 Workshop on Multi-modal Foundation Models and LLMs for Life Sciences (2025, Poster)

A systematic framework for predicting adverse drug reaction signals using medical data

Jeon, J., Hong, E., Kim, H. U.

AACR Annual Meeting, San Diego, USA (2024, Poster)

Predicting the signals of adverse drug reactions on the basis of medical data

Jeon, J., Hong, E., Kim, H. U.

AACR Annual Meeting, Orlando, USA (2023, Poster)

Predicting the effects of small molecules on transcriptome of cancer cell lines using deep learning

Jeon, J., Lee, S. M., Lee, G., Kim, H. U.

AACR Annual Meeting II, San Diego (virtual), USA (2020, Oral Presentation)

Preprints

Progressive Multi-Agent Reasoning for Biological Perturbation Prediction

Kim, H., Hwang, S.-Y., Lim, J., Piao, Y., Oh, Y., Kim, W. Y., Park, C., Ahn, S., & Jeon, J.^†

arXiv preprint arXiv:2602.07408 (2026)

^†corresponding author

Learning Adaptive Perturbation-Conditioned Contexts for Robust Transcriptional Response Prediction

Piao, Y., Kim, H., Kim, S., Oh, Y., Jeon, J., Hwang, S.-Y., Lim, J., Kim, W. Y., Park, C., & Ahn, S.

arXiv preprint arXiv:2602.18885 (2026)

Contact

Feel free to reach out for collaborations or discussions.

hyeok797@gmail.com