Research Overview
LSAIL investigates AI methods that are biologically grounded, practically useful, and scientifically reliable, while remaining broad enough to address diverse biological and biomedical problems.
Research Areas
AREA 01
AI for Computational Biology
Machine learning methods for understanding biological systems through molecular, cellular, and multi-omics data.
AREA 02
AI for Drug Discovery
Computational approaches for molecular discovery, virtual screening, candidate prioritization, and molecular design.
AREA 03
Biology-aware Representation Learning
Representations improved by transcriptomics, morphology, and other omics signals.
AREA 04
Multimodal Learning for Life Science
AI systems that bridge chemical and biological modalities for translational research.
Projects
TBD — Project title
Short description of the project (funder, timeline, collaborators, goal).
Resources
- Google Scholar
- TBD — GitHub / code repository
- TBD — Datasets / benchmarks