Abhishek Sarkar

I am a postdoctoral scholar at the University of Chicago working with Matthew Stephens.

I completed my Ph.D. at Massachusetts Institute of Technology in the Computational Biology group at the Computer Science and Artificial Intelligence Lab, advised by Manolis Kellis.


My main research interests are developing and extending cutting-edge machine learning techniques developed in problem domains outside of biology to gain insight into gene regulation and human disease.

Currently, I am working on methods to analyze single-cell genomic data and gain insight into the interplay between stochastic gene expression, genetic variation at quantitative trait loci, and transcription factor binding.

Previously, I developed methods to query how genetic variation which does not alter protein-coding sequences contributes to human disease. We integrate epigenomic information from the ENCODE and Roadmap Epigenomics consortia to identify cell-type–specific enhancers enriched for disease associated variants, and additional information about the transcriptional regulatory network to dissect their mechanistic role in psychiatric, metabolic, and autoimmune disorders. we then develop efficient Bayesian methods to understand the architecture of common diseases: how many causal genetic variants are there, where in the genome do they reside, and how should we design studies to more rapidly discover them in the population?


Peer-reviewed publications

Presentations (selected)

Technical reports