Research Experience

Multimodal AI Framework for High-Temperature Superconductors

July 2024 - Present

  • Collaborating with Dr. Ahmed Ragab from Polytechnique Montreal on developing a multimodal AI framework for predicting candidate high-temperature superconductors
  • Proposed a methodology integrating diverse data modalities like structural and compositional data to predict critical temperature (Tc)
  • Leveraged datasets such as SuperCon, Materials Project, ICSD, and Google’s GNoME dataset for building robust predictive models
  • Developing custom encoders (e.g., GNNs for crystal structures, CNNs for phase diagrams) and multimodal integration techniques involving these encoders
  • Exploring generative models for proposing new high-Tc materials, followed by validation through DFT methods and experimental collaboration
  • Research Poster presented at NeurIPS 2024 Tackling Climate Change with Machine Learning Workshop (Link)

Hybrid Modeling using Physics Informed Neural Networks

Jan 2023 - Present

  • Advisors: Prof. Richard Braatz, Prof. John R Williams, MIT
  • Collaborating with Dow Inc. (for industrial data) to build hybrid models for chemical processes
  • Working on modeling nonlinear processes like pH control, catalyst deactivation, and convective mass transfer
  • Incorporating physical constraints while optimizing process conditions using neural networks and other ML models
  • Manuscript under review by funding agency

Evaluating Machine Learned Interatomic Potentials for Disordered Rocksalts

Aug 2020 - Aug 2022

  • Advisor: Prof. Sai Gautam Gopalakrishnan, Indian Institute of Science
  • Analyzed the effects of dataset size and complexity on machine learning model training times
  • Compared different machine-learned interatomic potential models on disordered materials (DRX) datasets
  • Set-up and performed Density Functional Theory (DFT) calculations on 11,000+ cathode structures composed of 11 unique elements
  • Conducted hyperparameter optimization on all ML models used
  • Work accepted for Oral presentation at Materials Research Society (MRS) Spring Meet 2022
  • Published in Journal of Chemical Theory and Computation, 2024 (Link)

Detection and Tracking of Grain Boundaries in Polycrystalline Materials Using Scanning Transmission Electron Microscopy

May 2020 - July 2020

  • Microscopy Society of America, Undergraduate Research Scholarship
  • Research at University of California, Irvine (Did not happen due to COVID-19 travel and work restrictions)

Superlattices of covalently cross-linked 2D materials for the hydrogen evolution reaction

May 2019 - July 2019

  • Advisor: Prof. CNR Rao, FRS, JNCASR
  • Studied synthesis methods for 2D materials (Phosphorene, MoS2, Graphene)
  • Optimized functionalization of Phosphorene and synthesized covalent cross-links between Phosphorene with MoS2 and Graphene
  • Used Raman spectra, SEM, and TEM to confirm cross-linking between layers
  • Work published in APL Materials, 2020 (Link)

Effect of Porosity in CoCrMo and SS316L Additively Manufactured Superalloys

May 2018 - July 2018

  • Industry Internship Advisor: Dr. Dheepa Srinivasan, Intech Additive Solutions
  • Analyzed implant materials: Cobalt and Steel-based alloys for osteo-integration characteristics vs. strength
  • Evaluated ways to improve mechanical properties by modifying 3D printing parameters
  • Key skills learnt: Metallography, Microhardness, XRD, Optical Imaging, small-scale mechanical testing
  • Won Best Poster and Metallography Award at the 31st Annual MTE Department Symposium, IISc