Google Scholar
Education
PhD University of Maryland, College Park
About
Hirak Sarkar works across machine learning, algorithms, and cancer biology. His research deciphers the spatial architecture of complex diseases — how cells are arranged within a tissue, and how that arrangement drives disease progression — using probabilistic modeling and interpretable deep learning. His lab develops new inference methods for spatial transcriptomics and single-cell data, along with the compact data structures and indexes that make analysis at genomic scale practical, keeping pace with rapidly evolving sequencing and imaging technologies.
Sarkar joined Vanderbilt in 2025 from Princeton University, where he was a Ludwig Princeton Scholar. He earned his Ph.D. at the University of Maryland, College Park. He recently received a Vanderbilt-Ingram Cancer Center GI SPORE Career Enhancement Award, and a VICC P3 Cancer Innovation Accelerator award.
Research Focus
Computational Biology, Machine Learning
Publication Highlights
Terminus enables the discovery of data-driven, robust transcript groups from RNA-seq data
Joint imputation and deconvolution of gene expression across spatial transcriptomics platforms
Tumors hijack macrophages for iron supply to promote bone metastasis and anemia