Rohit Singh

Assistant Professor of Biostatistics & Bioinformatics

Rohit Singh is an Assistant Professor in the Departments of Biostatistics & Bioinformatics and Cell Biology at Duke Univ. His research interests are broadly in computational biology, with a focus on using machine learning to make drug discovery more efficient. Currently, he's exploring how single-cell genomics and large language models can help decode disease mechanisms and aid in identifying new targets and drugs. He is the recipient of the Test of Time Award at RECOMB, MIT's George M. Sprowls Award for his PhD thesis in Computer Science, and Stanford's Christopher Stephenson Memorial Award for Masters Research in the same field. In addition to academia, he has experience in the industry.

Appointments and Affiliations

  • Assistant Professor of Biostatistics & Bioinformatics
  • Assistant Professor of Cell Biology
  • Assistant Professor of Computer Science
  • Assistant Professor in the Department of Electrical and Computer Engineering
  • Member of the Duke Cancer Institute

Contact Information

Education

  • Ph.D. Massachusetts Institute of Technology, 2012

Research Interests

Drug discoveries have been instrumental in improving global health over the last century, but the median drug now takes about 10 years to bring to market and costs over a billion dollars to develop. My lab aims to expedite the development of precise diagnostics and therapeutics by applying machine learning. Our current work is broadly along two directions. Along the first direction, we use single-cell multiomics to discover regulatory mechanisms governing the interaction between the epigenome, transcription factors, and target genes. This approach relies on methodological innovation, developing new Granger causal inference techniques to capitalize on the “parallax” between simultaneous but separate measures of cell state. In the other direction, we apply large language models to model protein interaction and function. These protein language models enable powerful new approaches to predicting and understanding protein-protein and protein-drug interactions. 

Courses Taught

  • ECE 493: Projects in Electrical and Computer Engineering
  • ECE 391: Projects in Electrical and Computer Engineering
  • COMPSCI 394: Research Independent Study
  • COMPSCI 393: Research Independent Study
  • CELLBIO 493: Research Independent Study

In the News

Representative Publications

  • Erden, Mert, Xuting Zhang, Kapil Devkota, Rohit Singh, and Lenore Cowen. “Learning a PRECISE language for small-molecule binding.” OpenRxiv, January 5, 2026. https://doi.org/10.64898/2026.01.04.697581.
  • Wu, Alexander P., Rohit Singh, Christopher A. Walsh, and Bonnie Berger. “Unveiling causal regulatory mechanisms through cell-state parallax.” Nat Commun 16, no. 1 (August 29, 2025): 8096. https://doi.org/10.1038/s41467-025-61337-5.
  • Sledzieski, Samuel, Charlotte Versavel, Rohit Singh, Faith Ocitti, Kapil Devkota, Lokender Kumar, Polina Shpilker, et al. “Decoding the Functional Interactome of Non-Model Organisms with PHILHARMONIC.,” August 25, 2025. https://doi.org/10.1101/2024.10.25.620267.
  • O’Neil, E. V., S. M. Dupont, R. Singh, and B. Capel. “The basic helix-loop-helix transcription factor TCF4 recruits the Mediator Complex to activate gonadal genes and drive ovarian development.” BioRxiv, July 11, 2025. https://doi.org/10.1101/2025.02.28.640455.
  • Keenen, Madeline M., Liheng Yang, Huan Liang, Veronica J. Farmer, Rizban E. Worota, Rohit Singh, Amy S. Gladfelter, and Carolyn B. Coyne. “Comparative analysis of the syncytiotrophoblast in placenta tissue and trophoblast organoids using snRNA sequencing.” ELife 13 (May 27, 2025). https://doi.org/10.7554/elife.101170.3.