My Research

My current work lies on the interface of implementing Deep Learning (DL) techniques, running multi-scale high performance accelerated simulations and performing scattering experiments (especially neutron and X-Ray) for problems related to soft matter systems especially Biomedical and biological sciences, and to make new drug molecules with desired properties. The broader goal is to find how the DL techniques can be optimally applied to the multi-scale modeling and simulation coupled with scattering experiments to understand the underneath physics of bio(macro)molecular function, activity, folding, microscopic structure and dynamic behavior at different length and time scale and whether that knowledge could lead to designing new therapeutics. Additionally, I am trying to develop tools to study large-scale datasets by learning the inherent hidden features of biomolecules in order to reduce the need for running expensive computation or experiments.

Interestes

  • Domain
    • Biological/ Biomedical Science
    • Complex/ Disordered system
    • Polymer/ Polyelectrolytes
    • Soft matter
    • Proteomics
    • Gene editing
  • Techniques
    • Scattering: specially Neutron/ X-ray/ Light
    • Simulation: specially Molecular Dynamics/ Atomistic/ Agent Based
    • Modelling
    • Data Analytics
    • Deep Learning

Media

  • News/ Highlights

    • 2021: Countering COVID:
      News in ASCR Discovery: Advances Science through Computing

    • 2021: Using GANs with adaptive training data to search for new molecules
      highlight in Computational Sciences and Engineering

    • 2020: The hanging heart: How KRAS lures its prey to the membrane
      Commentary on The Proceedings of the National Academy of Sciences (PNAS), the official journal of the National Academy of Sciences (NAS)

    • 2020: Bhowmik applies supercomputing, AI to analyze COVID-19
      news in ORNL Today

    • 2020: New Studies Highlight MCS Physics Group’s Innovative Contributions to Cancer Research
      news in Mellon College of Science, Carnegie Mellon University

    • 2020: Learning Life’s ABCs: AI Models Read Proteins to Fight COVID-19 | Researchers are closing the accuracy gap for a new class of biology tools based on natural-language processing
      Highlights in nvidia and featured in blogs.nvidia.com

    • 2019: Modified deep-learning algorithms unveil features of shape-shifting proteins
      Highlights in Oak Ridge National Laboratory (ORNL) and featured in News Reports, Scientific articles

    • 2018: Molecular shape dictates the dynamic course in narrow channels
      Highlights in Advances in Engineering

    • 2017: Diamonds that deliver: Neutrons, simulation analysis of tRNA-nanodiamond combo could transform drug delivery design principles
      Highlights in Oak Ridge National Laboratory (ORNL), US Department of Energy (DOE) Office of Science (SC); mentioned by Under Secretary of Energy for Nuclear Security and Administrator for the National Nuclear Security Administration of the U.S. Department of Energy; and featured in numerous News Reports, Scientific articles, blogs, Twitter, Facebook posts

    • 2015: Quasielastic neutron scattering insight into the molecular dynamics of all-polymer nano-composites featured as Neutron Research: Application Examples for Soft Condensed Matter for Heinz Maier-Leibnitz Zentrum (MLZ)/FRM II, Neutrons for Research, Industry and Medicine