Welcome to Yongchan Hong’s Webpage
Hi, I’m a PhD student in the Department of Quantitative and Computational Biology at the University of Southern California, advised by Vsevolod Katritch and Yan Liu. I am currently also working with the Ellison Medical Institute as a visiting student researcher. Prior to my PhD, I obtained my bachelor’s degree in Mathematical and Computational Biology at Harvey Mudd College. Between my bachelor’s studies, I returned to Korea to serve my mandatory military service and worked as a software engineer at various companies, including Krust Universe and Krafton.
Research
My research focuses on building “reliable” computational drug discovery along three directions:
- Creating reliable benchmarks and training datasets
- Integrating physics and chemistry information inside models
- Using uncertainty quantification and Bayesian optimization
I’m always happy to chat with anyone interested in the computational drug discovery field — please reach out!
Contact
Email: hongyong [at] usc [dot] edu
News
- September 2026: Our short paper “Can Self-Improving Agents Recover Cofolding Failures?” was accepted at NeurIPS 2026 AgenticLS!
- September 2026: Gave a presentation at the Ellison Medical Institute on my work in “PRETZEL: A Benchmark for Cyclic Peptide Structure Prediction”.
- August 2026: Our paper “Trustworthy Protein–Ligand Binding Affinity Prediction via Reliability-Aware Multi-Engine Fusion” received an Outstanding Paper Award at KDD 2026 RelSciFM!
- May 2026: Our paper “Trustworthy Protein–Ligand Binding Affinity Prediction via Reliability-Aware Multi-Engine Fusion” was accepted at KDD 2026!
- May 2026: Our paper “GLACIER: A Multimodal Student-Teacher Foundation Model for Molecular Property Prediction” was accepted at KDD 2026!