26 citations · 36 across the 12 of their papers we have counts for
4 papers · 1 filter
Natural-Language-Guided Generator-Agnostic Shortlisting for Protein Binder Design
Gyubok Lee, Kiwoong Yoo, Jimin Seo +3
Modern de novo design workflows generate many candidate protein binders, but wet-lab validation capacity remains limited, making shortlisting a major bottleneck. We study whether L…
Leveraging Biokinetic Knowledge Priors for Data-Scarce Bioprocess Modeling
Kyunghoon Hur, Eunjung Jeon, Hyun Woo Kim +2
While deep learning has accelerated drug discovery, its impact on biomanufacturing has been considerably more limited. The reason is data scarcity. Bioreactor experiments are high-…
Compressing the Validation Bottleneck: An Agentic Self-Driving Lab for Scientific Discovery
Kyunghoon Hur, Chihun Lee
Agentic AI-for-Science can automate ideation, planning, and analysis, but final validation still depends on real experiments. A self-driving lab (SDL) can execute those experiments…
Multi-lingual Multi-institutional Electronic Health Record based Predictive Model
Kyunghoon Hur, Heeyoung Kwak, Jinsu Jang +2
Large-scale EHR prediction across institutions is hindered by substantial heterogeneity in schemas and code systems. Although Common Data Models (CDMs) can standardize records for…