Research Interests: Development of computational and data-driven methods for ab initio material modelling at larger length and time-scales, Finite-element methods and HPC-centric algorithms for PAW (projector-augmented wave) formalism in DFT, Applications to energy-storage materials, Lead developer of Gordon Bell Prize-winning DFT-FE open-source code.
Read more about Kartick's work in his webpage
Research Interests: Novel finite-element based computational methods for large-scale quantum modelling of materials incorporating magnetism and spin-orbit coupling, Applications to ab initio modeling of device materials, Mixed precision eigensolvers, Large-scale scientific computing, Quantum Computing based algorithms, Lead developer of Gordon Bell Prize winning DFT-FE open-source code.
Read more about Nikhil's work in his webpage
Research Interests: Hardware-aware matrix-free algorithms for accelerating iterative eigenvalue solvers and linear solvers on heterogenous architectures, Applications to solvers employed in quantum modeling of materials, High-performance computing, Low-level CUDA kernel programming on modern GPU architectures, Contributor to Gordon Bell Prize winning DFT-FE open-source code.
Read more about Gourab's work in his webpage
Research Interests: Fast and scalable computational methods for meta-GGA DFT functionals, Preconditioned mixing schemes for non-linear eigenvalue problems arising in quantum modelling of materials, Time propagator type methods for accelerating real-space DFT problems on classical computers and quantum computers.
Contributor to Gordon Bell Prize winning DFT-FE open-source code
Read more about Srinibas's work in his webpage
Research Interests: HPC and AI accelerated methods for ab initio calculations, Computational methods for accelerating DFT calculations using implicit solvation models. Contributor to Gordon Bell Prize winning DFT-FE open-source code
Research Interests: Real-space computational methods for ab initio modelling of magnetic materials using DFT-FE, TD-DFT, Quantum computing
Research Interests: Multiscale modeling, Reactive molecular dynamics, combustion physics
Research Interests: Real-space finite-element computational methods for non-local vDW DFT functionals, Ab-initio modeling of functional materials.
Harshit Rawat (Joined Aug 2024)
Education: BS Mathematics and Physics, IIT Kanpur, 2023
Dissertation Project Topic: Novel fine-tuning and distillation strategies with graph neural networks for accelerated materials discovery
Naman Pesricha (Joined Aug 2024)
Education: B.Tech Mechanical Engineering, IIT Roorkee, 2023
Dissertation Project Topic: Parallel Algorithms for Tensor Decompositions
Webpage: https://pesricha.github.io/
Interests: Battery interface modeling using ML workflows with DFT-FE, ASE interface to DFT-FE
Rudra Panch, B.Tech IIT Madras (Intern: June 2024 - June 2025)
[Currently working at Hero Honda Motors]
Kartikeya Srivastava, B.Tech BITS Pilani (Intern and Project Associate at MATRIX Lab: Aug 2022 - May 2024)
[Currently PhD student at UCLA, USA]
Gourab Panigrahi, BS IISc Bangalore (Project Associate: Sept 2020 - July 2021)
[Currently PhD student at IISc, Bangalore]
Debashis Panda, B.Tech BITS Hyderabad (Project Associate: Sept 2020 - July 2021)
[Currently PhD student at Imperial College, UK]
Kishore Nori, B.Tech IIT Guwahati (Project Associate: April 2021 - Jan 2022)
[Currently PhD student at Monash University, Australia]
Rushikesh Pawar (M.Tech CDS: Aug 2023 - June 2025) [Currently at Observe.Ai, Bangalore]
Dissertation Project Topic:
Test time domain adaptation frameworks using equivariant graph neural networks for accelerated materials discovery.
Nihar Shah (M.Tech CDS: Aug 2023 - June 2025) [Currently at LTI Mindtree, Bangalore]
Dissertation Project Topic:
A Hybrid quantum-classical algorithm for solving large sparse linear eigenvalue problems
Sundaresan (M.Tech CDS: Aug 2022 - June 2024) [Currently at Intel Research Labs, Bangalore]
[Institute Motorola Medal for highest CGPA and grade in dissertation project]
Dissertation Project Topic:
Communication-optimal parallel slicing algorithm for iterative solution of large-scale sparse eigenvalue problems.
Sayan Datta (M.Tech CDS: Aug 2022 - June 2024) [Currently at Qualcomm, Bangalore]
Dissertation Project Topic:
Efficient graph neural network frameworks for accelerated atomic force and energy predictions in molecular systems
Ashish Rout (M.Tech CDS: Aug 2021 - June 2023) [Currently at Target, Bangalore]
[Reliance Foundation Fellow, Institute Motorola Medal for highest CGPA and grade in dissertation project)
Dissertation Project Topic:
Robust lightweight graph neural network-based frameworks for accelerating crystal structure prediction
Sameer Raju Khadatkar (M.Tech CDS: Oct 2020 - June 2022) [Currently at Wells Fargo, Hyderabad]
[CDS Honorable mention award for excellent CGPA and grade in dissertation project)
Dissertation Project Topic: