Appointment: Assistant Professor

Research topics:

• To use computational tools from PDE, differential geometry, algebraic topology and statistical learning to study the biomolecular structure, flexibility, dynamics, and functions.
• Topological data analysis (TDA), topology based machine learning/deep learning models, and their applications in drug design.

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1 to 2 of 2 Results
Replication Data for: Hypergraph based persistent cohomology (HPC) for molecular representations in drug design
Apr 6, 2021
Xia, Kelin, 2021, "Replication Data for: Hypergraph based persistent cohomology (HPC) for molecular representations in drug design", https://doi.org/10.21979/N9/16CFBW, DR-NTU (Data), V2
Artificial intelligence (AI) based drug design has demonstrated great potential to fundamentally change the pharmaceutical industries. Currently, a key issue in AI-based drug design is efficient transferable molecular descriptors or fingerprints. Here, we present hypergraph-based...
Replication Data for: Ollivier Persistent Ricci Curvature-Based Machine Learning for the Protein–Ligand Binding Affinity Prediction
Replication Data for: Ollivier Persistent Ricci Curvature-Based Machine Learning for the Protein–Ligand Binding Affinity Prediction
Apr 2, 2021
Xia, Kelin, 2021, "Replication Data for: Ollivier Persistent Ricci Curvature-Based Machine Learning for the Protein–Ligand Binding Affinity Prediction", https://doi.org/10.21979/N9/JHXLSG, DR-NTU (Data), V1
Efficient molecular featurization is one of the major issues for machine learning models in drug design. Here, we propose a persistent Ricci curvature (PRC), in particular, Ollivier PRC (OPRC), for the molecular featurization and feature engineering, for the first time. The filtr...
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