Overview
Computational immunology (stochastic and spatial models and simulations, T cell signaling, immune regulation)
Statistical methodology for immunological laboratory techniques (flow cytometry, CFSE analysis, receptor-ligand binding and signaling kinetics)
Informatics of the immune system (reference and application ontologies, meta-programming, text mining and machine learning)
Statistical methodology for immunological laboratory techniques (flow cytometry, CFSE analysis, receptor-ligand binding and signaling kinetics)
Informatics of the immune system (reference and application ontologies, meta-programming, text mining and machine learning)
Current Duke Appointments & Affiliations
Professor of Biostatistics & Bioinformatics
·
2022 - Present
Biostatistics & Bioinformatics, Division of Integrative Genomics,
Biostatistics & Bioinformatics
Research Professor of Statistical Science
·
2022 - Present
Statistical Science,
Trinity College of Arts & Sciences
Research Professor of Mathematics
·
2025 - Present
Mathematics,
Trinity College of Arts & Sciences
Member of the Duke Cancer Institute
·
2019 - Present
Duke Cancer Institute,
Institutes and Centers
Recent Scholarly Works
Polygenic risk scores and HLA class II variants are biomarkers of corticosteroid response in childhood nephrotic syndrome.
Journal article Kidney Int · June 2026 INTRODUCTION: Nephrotic syndrome (NS), a common glomerular disease in children, is classified based on response to corticosteroid therapy as either steroid-sensitive nephrotic syndrome (SSNS), or steroid-resistant nephrotic syndrome (SRNS). However, there ... Full text Link to item CiteProfiling Allogeneic HLA-specific B-cell Responses Utilizing a 64-plex Single-HLA Reporter Cell Panel.
Preprint · January 20, 2026 Identifying allogeneic HLA-specific B cells in sensitized individuals is essential for defining the cellular basis of allogeneic humoral immunity but remains technically challenging due to their low frequency. To overcome this barrier, we generated a 64-pl ... Full text Link to item CiteSingle-cell and spatial detection of senescent cells using DeepScence.
Journal article Cell Genom · December 10, 2025 Accurately identifying senescent cells is essential for studying their spatial and molecular features. We developed DeepScence, a method based on deep neural networks, to identify senescent cells in single-cell and spatial transcriptomics data. DeepScence ... Full text Link to item CiteRecent Grants
Computational Biology and Bioinformatics Training Grant
Inst. Training Prgm or CMEMentor · Awarded by National Institutes of Health · 2026 - 2031Interdisciplinary Research Training Program in AIDS
Inst. Training Prgm or CMEMentor · Awarded by National Institutes of Health · 2010 - 2030Center for Multiscale Immune Systems Modeling
ResearchPrincipal Investigator · Awarded by National Institute of Allergy and Infectious Diseases · 2025 - 2030View All Grants
Education
University College London (United Kingdom) ·
2002
Ph.D.
University College London (United Kingdom) ·
1998
M.S.
University of London (United Kingdom) ·
1997
B.S.
National University of Singapore (Singapore) ·
1991
M.B.B.S.