Research

PhD Research

Graduate Research Assistant
  • uFlowCSP: single-step generative model for crystal structure prediction. Discovering a new material starts with predicting how its atoms pack together, and the generative models that do this well are slow: every candidate structure costs hundreds to thousands of sequential network calls, so screening a chemical space burns hours of GPU time. I built a model that produces a complete crystal in one network evaluation by learning the average velocity of the generative trajectory instead of the instantaneous one. A screening run of ten thousand candidates drops from over an hour to under a minute, with accuracy that matches or beats the multi-step models it replaces. The hard part was conditioning: a Transformer over atoms with chemistry-aware ordering and composition features, plus a symmetry signal used only during training, so the deployed model needs nothing but a chemical composition to run.
    • Machine learning pipeline for crystal generation
    Animation: uFlowCSP turns random noise into a crystal structure in one step
  • Polyhedron topology based mapping algorithm for polymorphic crystal structures - I developed polyhedron connectivity based graph topology to cluster materials across diverse space groups, improving identification of structural similarities beyond symmetry-based methods. Paper link.
    • Polyhedron topology based mapping visualization
    Animation: polymorphs regrouped from space groups into polyhedral-topology clusters
  • Developed a variant of Atomistic Line Graph Neural Network (ALIGNN) model by Δ-learning electronic structure of crystals to predict HSE eigenvalues, a key opto-electronic property. By leveraging inexpensive PBE calculations and orbital projections, I could build highly accurate ML model as surrogate for costly DFT calculation.
    • Animation: Delta-learning corrects PBE band gaps toward HSE values
    August 2021 - Present

    MS Research

    Graduate Research Assistant

    I automated the AI powered Laser-Induced Graphene Process(LIG) manufacturing using Bayesian Optimization. The automated system is generalized and can be deployed to manufacture other materials.

    Animation: Bayesian-optimization active learning finds the best laser settings for graphene
    August 2019 - July 2021

    Undergraduate Thesis

    Formant-based Perceptual Space Classification is focused on detecting the Bengali vowel from continuous speech. High Accuracy by SVM RBF Kernel Classifier is gained. This will enhance the emotional state recognition research in the Bengali language.

    June 2017 - May 2018