From molecular data to meaningful discovery.

“The essence of my research vision is to transcend the complexity of our living systems to achieve a deep understanding of how molecular interactions, protein regulatory states, and cellular environments shape drug responses and biomolecular functions. Drawing on my interdisciplinary background in chemistry, biochemistry, and computer science, I aim to establish a convergence research framework by developing machine learning/deep learning models, methods, and frameworks that integrate molecular representation learning, multimodal biological data, biomolecular modeling, and physics-based simulations. By connecting computational innovation with biological insights, I aspire to unravel fundamental biological problems to advance mechanistic understanding that supports applications in structural and systems biology, and translate atomistic and molecular-scale discoveries toward improved therapeutic discovery and design for human health.”