Pranam D. Chatterjee

Assistant Professor of Biomedical Engineering

Appointments and Affiliations

  • Assistant Professor of Biomedical Engineering
  • Assistant Professor in Biostatistics & Bioinformatics
  • Assistant Professor of Computer Science
  • Member of the Duke Cancer Institute

Contact Information

  • Office Location: 101 Science Drive, Ciemas 2353A, Durham, NC 27705
  • Office Phone: +1 706 442 2715
  • Email Address:
  • Websites:


  • Ph.D. Massachusetts Institute of Technology, 2020

Research Interests

Integration of computational and experimental methodologies to design novel proteins for applications in genome editing, targeted protein modulation, and reproductive bioengineering

Courses Taught

  • EGR 393: Research Projects in Engineering
  • COMPSCI 590: Advanced Topics in Computer Science
  • COMPSCI 394: Research Independent Study
  • BME 791: Graduate Independent Study
  • BME 789: Internship in Biomedical Engineering
  • BME 590: Special Topics in Biomedical Engineering
  • BME 494: Projects in Biomedical Engineering (GE)
  • BME 493: Projects in Biomedical Engineering (GE)
  • BME 390L: Special Topics with a Lab

In the News

Representative Publications

  • Zhang, Yinuo, Phil He, Ashley Hsu, and Pranam Chatterjee. “MetaLATTE: Metal Binding Prediction via Multi-Task Learning on Protein Language Model Latents.” Cold Spring Harbor Laboratory, June 29, 2024.
  • Vincoff, Sophia, Shrey Goel, Kseniia Kholina, Rishab Pulugurta, Pranay Vure, and Pranam Chatterjee. “FusOn-pLM: A Fusion Oncoprotein-Specific Language Model via Focused Probabilistic Masking.,” June 4, 2024.
  • Peng, Zhangzhi, Benjamin Schussheim, and Pranam Chatterjee. “PTM-Mamba: A PTM-Aware Protein Language Model with Bidirectional Gated Mamba Blocks.” BioRxiv, 2024.
  • Chen, T., L. Hong, V. Yudistyra, S. Vincoff, and P. Chatterjee. “Generative design of therapeutics that bind and modulate protein states.” Current Opinion in Biomedical Engineering 28 (December 1, 2023).
  • Brixi, Garyk, Tianzheng Ye, Lauren Hong, Tian Wang, Connor Monticello, Natalia Lopez-Barbosa, Sophia Vincoff, et al. “SaLT&PepPr is an interface-predicting language model for designing peptide-guided protein degraders.” Communications Biology 6, no. 1 (October 2023): 1081.