Mihir Bafna

I am an incoming Ph.D. student in EECS at MIT, interested in research at the intersection of machine learning and structural biology, specifically with generative modeling. Additionally, I continue to be excited by advances in single cell genomics and how graph representation learning can be utilized. My research is partially supported by the NSF Graduate Research Fellowship Program (GRFP).

Previously, I completed my B.S. in CS at Georgia Tech specializing in Machine Learning and Theory. I was incredibly fortunate to have been advised by Xiuwei Zhang (Georgia Tech), Jian Ma (CMU), Ruochi Zhang (Broad), and Bonnie Berger (MIT).

selected publications


  1. DiffRNAFold
    NeurIPS MLSB
    DiffRNAFold: Generating RNA Tertiary Structures with Latent Space Diffusion
    Mihir Bafna, Vikranth Keerthipati, Subhash Kanaparthi, and Ruochi Zhang
    In NeurIPS Workshop on Machine Learning for Structural Biology (NeurIPS MLSB) Dec 2023
  2. Clarify
    ISMB
    CLARIFY: Cell-cell interaction and gene regulatory network refinement from spatially resolved transcriptomics
    Mihir BafnaHechen Li, and Xiuwei Zhang
    ISMB and Bioinformatics Jun 2023
  3. DeepVifi
    ACM-BCB
    DeepViFi: Detecting Oncoviral Infections in Cancer Genomes Using Transformers
    Utkrisht Rajkumar, Sara Javadzadeh,  Mihir Bafna, Dongxia Wu, Rose Yu, Jingbo Shang, and Vineet Bafna
    In Proceedings of the 13th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics (ACM-BCB) Jun 2022
  4. MetaDetect
    Computer-implemented methods for quantitation of features of interest in whole slide imaging
    Nam Nguyen, Lorena Mora-Blanco, Kristen Turner, Julie Weise, Jason Christiansen, and Mihir Bafna
    Provisional patent. PCT/US2021/022308 Mar 2021