Debswapna Bhattacharya

I am an Associate Professor in the Department of Computer Science at Virginia Tech (VT). My primary research interests are computational biology and applied machine learning with a particular focus on AI-powered molecular modeling. I am also interested in applications of data science in bioinformatics. My recent projects are focused on developing data-driven machine learning and optimization algorithms to elucidate complex relationships between macromolecular sequences, structures, functions, interactions, and pathways. I am a recipient of the NSF CAREER Award (2020), NIH Maximizing Investigators' Research Award (MIRA) (2020), AU Ginn Faculty Achievement Fellowship (2020), AU Outstanding CSSE Faculty Award (2019), and MU Outstanding CS Ph.D. Student Award (2014).

Before joining VT, I worked as an Assistant Professor at Auburn University (2017 to 2021) and at Wichita State University (2016 to 2017). I obtained my Ph.D. in Computer Science from the University of Missouri - Columbia in 2016 under the supervision of Prof. Jianlin Cheng.

Office: 2160N Torgersen Hall
620 Drillfield Drive
Blacksburg, VA 24061
Phone: (540) 231-2865
Fax: (540) 231-6075


Prospective Ph.D. Students:
We are actively looking for new Ph.D. students. If you are interested, please apply through the CS at VT Ph.D. admissions process by marking my name in your application package and complete this brief form here.

Prospective Post-Doctoral Researchers:
We are actively looking for post-doctoral researchers. If you are interested, please complete this brief form here and send me an email at

Important Note: If you are interested in working with us, the best thing to do is to read several of our recent papers to get a sense of our research and figure out mutual interest. Please understand that we receive a lot of emails/applications, and we may not be able to respond to inquiries that do not exhibit a clear match.

Selected Recent Publications (Full List)

  • DisCovER: distance- and orientation-based covariational threading for weakly homologous proteins
    Sutanu Bhattacharya, Rahmatullah Roche, Debswapna Bhattacharya*
    PROTEINS: Structure, Function, and Bioinformatics, doi: 10.1002/prot.26254, 2021

  • DeepRefiner: high-accuracy protein structure refinement by deep network calibration
    Md Hossain Shuvo, Muhammad Gulfam, Debswapna Bhattacharya
    Nucleic Acids Research, Web Server Issue, 49(W1): W147-W152, 2021

  • Hybridized distance- and contact-based hierarchical structure modeling for folding soluble and membrane proteins
    Rahmatullah Roche, Sutanu Bhattacharya, Debswapna Bhattacharya
    PLOS Computational Biology, 17(2): e1008753, 2021

  • QDeep: distance-based protein model quality estimation by residue-level ensemble error classifications using stacked deep residual neural networks
    Md Hossain Shuvo, Sutanu Bhattacharya, Debswapna Bhattacharya
    Intelligent Systems for Molecular Biology (ISMB), 2020
    Bioinformatics, 36(S1): i285-i291, 2020

  • refineD: improved protein structure refinement using machine learning based restrained relaxation
    Debswapna Bhattacharya
    Bioinformatics, 35(18): 3320-3328, 2019

Copyright © Debswapna Bhattacharya 2021