About me

I love watching most sports and playing a few of them too. I worked on devleoping multiscale modeliing theories and methods for a wide range of materials such as polymer, carbon nanotubes, collagen fibers, ceramics and metals during my Ph.D. I also worked on machine learning and data science to develop computational tools for materials science. I am currently working at Applied Materials, Inc. as an Algorithm Developer.

Computational Tools

  1. Computational X-ray Photon Correlation Spectroscopy (C-XPCS)
  2. Testbed for Machine-learned Force Fields (TB-MLFF)
  3. SP Statistics of Polymer Networks (PolyBranchX)
  4. Preparation of Polymer Networks (POLYMER_MD)

Publications

  1. Generalizability of Graph Neural Network Force Fields for Predicting Solid‐State Properties
  2. On the First Passage Times of Branching Random Walks in Rd
  3. Network evolution controlling strain-induced damage and self-healing of elastomers with dynamic bonds
  4. Modeling Shortest Paths in Polymeric Networks using Spatial Branching Processes
  5. Development of scalable and generalizable machine learned force field for polymers
  6. Evaluating the transferability of machine-learned force fields for material property modeling
  7. Computational approaches to model X-ray photon correlation spectroscopy from molecular dynamics
  8. High energy density flexible and ecofriendly lithium-ion smart battery
  9. Stress-electrochemistry interactions in a composite electrode for Li-ion batteries
  10. A phase-field model for crack growth in electro-mechanically coupled functionally graded piezo ceramics
  11. An analytical model for shape morphing through combined bending and twisting in piezo composites
  12. Understanding Urban Water Consumption Using Remotely Sensed Data
  13. Stockbot: Using LSTMs to predict stock prices
  14. A Finite Strain Based Coupled Chemo-Mechanical Study of the Anode Materials in Lithium-ion Batteries