1). Multimodal AI for biomedical data
2). Multimodal causal inference
3). Wearable and digital health
4). Real-world data using TriNetX, Digital pathology and spatial omics
The Mallick Lab develops scalable computational and AI methods to integrate multimodal data, uncover disease mechanisms, and generate actionable hypotheses that advance biomarker discovery and precision medicine.
The Mallick Lab focuses on developing biologically and clinically informed statistical and computational methods to accelerate the translation of discoveries from bench to bedside. In recent years, my work has spanned several major areas: (a) discovery of clinically actionable biomarkers from integrated multi-omics profiles to enable improved disease outcome prediction and patient stratification; (b) analysis of health information related to the human microbiome, as well as molecular measurements of microbial communities in epidemiological populations; (c) uncertainty-aware multimodal AI; (d) design, implementation, and analysis of biomarker-based randomized controlled trials and molecular epidemiology studies; and (e) digital pathology and computational image analysis.
Biography
Dr. Himel Mallick is an Assistant Professor of Population Health Sciences, with a secondary appointment in GI, specializing in AI/ML and omics data science. The Mallick Lab develops multimodal AI approaches to uncover mechanisms underlying complex human diseases. By building scalable statistical methods and collaborating across clinical and biological domains, the lab aims to advance precision medicine and improve human health.
Distinctions:
Young Alumni Rising Star Award, University of Alabama at Birmingham
Elected Fellow, American Statistical Association
Elected Fellow, International Statistical Institute
Elected Fellow, International Indian Statistical Association (IISA)
Early Career Award in Statistics and Data Sciences (ECASDS) Award Winner
Associate Director (Associate Principal Scientist), Merck Research Laboratories (MRL)
Associate Editor for Sankhya B, Frontiers in Genetics, and SAGMB
Statistical Reviewer for Hepatology Communications, Liver Transplantation, and The Lancet Psychiatry
