PhD researcher · Purdue ECE

Sanjeev Khare

I build computational models to study magnetic and ferroelectric materials, combining condensed matter physics with high-performance scientific computing in Julia.

Sanjeev Khare

Electrical & Computer Engineering
Purdue University

About

From material physics to scientific software

I am a PhD researcher in Electrical & Computer Engineering at Purdue University, working at the intersection of condensed matter physics and high-performance scientific computing. My dissertation, Phase Field Modelling of Quantum Metamaterials, is supervised by Prof. Pramey Upadhyaya.

I combine analytical models with Julia simulations to study magnetic order and ferroelectric polarization. Before Purdue, I designed satellite electronics at ISRO and established a semiconductor device characterization lab.

More about my background

Quick Facts

Purdue University, West Lafayette, IN
Ph.D. in progress · 2023 – present
Advisor: Prof. Pramey Upadhyaya
Primary language: Julia
Interests: computational physics & scientific ML
Research

Current focus areas

Noncollinear spin order · conceptual schematic
Noncollinear spin order · conceptual schematic
01

Chiral Antiferromagnet Spin Dynamics

I study how currents control noncollinear magnetic order in Mn₃Pt-type chiral antiferromagnets. Analytical models and numerical simulations reveal spin dynamics, switching paths, and the effects of current-induced torques.

Mn₃PtLLGSNEB/CI-NEBGLMakieStaticArrays.jl
Explore selected work
Opposing polarization domains · conceptual schematic
Opposing polarization domains · conceptual schematic
02

Ferroelectric Phase-Field Simulations

I develop phase-field simulations to study how polarization textures evolve and respond to excitation in STO/PTO ferroelectric structures. Spectral numerical methods couple polarization dynamics with electrostatics.

LK equationETD2RKSTO/PTOFerronsSpectral methods
Simulation tools
Learning with physical constraints · conceptual workflow
Learning with physical constraints · conceptual workflow
03

ML for Physics & Model Discovery

I explore physics-informed neural networks and neural operators for model discovery and surrogate modeling of dynamical systems, using physical constraints to guide learning from data.

PINNsFNODeepONetLux.jl
Read the paper
Two rotated lattices · conceptual schematic
Two rotated lattices · conceptual schematic
04

Moiré Micromagnetics

I use micromagnetic simulations to study how twisting magnetic layers changes their spin textures, investigating noncollinear magnetic phases and domain walls in moiré materials.

Moiré latticeMicromagneticsOVF formatJulia
Read the preprint
Selected work

From a physical question to a computational tool

Publications

Publications & preprints

Preprint · arXiv
Chang Niu, Kisoo Nam, Aravindh Shankar, Jian-Yu Lin, Sanjeev Khare, Sumi Lee, Pramey Upadhyaya, & Peide D. Ye
arXiv:2608.09283 · cond-mat.mes-hall · August 2026

Direct density-of-states mapping probes size-dependent localization in oxide semiconductors.

Read summary

Lock-in electric-field penetration is used to map the effective density of states in In-based oxide semiconductor TFTs, showing that band-tail states become screening- and transport-active. Geometry-dependent DOS mapping reveals exponential suppression of the effective DOS with channel length — a microscopic origin of localization-induced threshold-voltage roll-off — and that disorder can be tuned via thickness, O₂ annealing, and In/Ga/Zn composition.

Preprint · arXiv
Guanghui Cheng, Shiva T. Konakanchi, Andres E. Llacsahuanga Allcca, Sanjeev Khare, Nithin Abraham, Yuqing Cao, Hechang Lei, Kenji Watanabe, Takashi Taniguchi, Pramey Upadhyaya, & Yong P. Chen
arXiv:2606.00604 · cond-mat.mes-hall · May 2026

Twisting magnetic layers produces noncollinear spin textures and 90° domain walls.

Read summary

Twisted CrCl₃ XY magnets host robust noncollinear moiré magnetism, with field-driven transitions from coexisting AFM and FM domains that persist up to double nine-layer stacks. Combined with micromagnetic simulations, the ground state is identified as the predicted “twisted-s” phase with 90° domain walls, and these phases are shown to be electrically tunable.

Nitin Tiwari, R.V.B.S. Raghavamsi, Sanjeev Khare, & Boonam Shin
Computers and Geotechnics · Vol. 197 · 108180 · Elsevier · September 2026

Short-time Fourier synthesis addresses spectral bias in physics-informed viscoelastic modeling.

Read summary

Spectral bias — the tendency of neural networks to learn low-frequency components while missing high-frequency transients — limits PINNs for viscoelastic characterization of pavement geomaterials under time-varying loading. We developed a spectral temporal synthesis framework using inverse Short-Time Fourier Transform (iSTFT) operations, with learnable complex-valued spectral–temporal representations, to enable physics-informed learning of viscoelastic operators across millisecond-to-second timescales.

Rastogi G., Chaitanya M.K., Khare S., Yadav E., Kaneriya R.K., Upadhyay R.B., et al., & Bhattacharya A.N.
Microelectronic Engineering · Vol. 249 · 111617 · 2021
Open Source & Research Code

Scientific software & research tools

Simulation software, numerical methods, and visualization tools. Public repositories include a direct link. Other projects are research tools with no public repository linked here.

SkewedAxisFourierAnalysis.jl

Fourier analysis along skewed/non-orthogonal axes — useful for moiré superlattice computations and reciprocal-space analysis of twisted heterostructures.

JuliaPublic · MIT
View repository ↗

ChiralAFM

Three-sublattice spin dynamics for chiral antiferromagnets (Mn₃Pt). Includes NEB/CI-NEB solvers, collective-coordinate LLGS projection, SOT/STT torques, and GLMakie energy landscape visualization.

JuliaResearch code

No public repository linked

FerroElectricScripts.jl

Spectral ETD2RK + FFT solver for the Landau-Khalatnikov equation. Supports patterned contacts, Strang-split sponge boundaries, and ferron dispersion analysis in STO/PTO superlattices.

JuliaResearch code

No public repository linked

More research tools & development setup

RapidSolver.jl

High-performance ODE/DAE solver infrastructure for large-scale scientific simulations on HPC clusters, optimized for memory efficiency and parallel execution.

JuliaResearch code

No public repository linked

OvfViewer

Reader and GLMakie-based visualizer for OOMMF Vector Field (.ovf) files produced by micromagnetic simulations — 3D magnetization field inspection with interactive slicing.

JuliaResearch tool

No public repository linked

moire_micromagnetic_simulation

Simulation suite for moiré quantum material systems. Used to discover novel magnetization modes in twisted magnetic heterostructures arising from moiré superlattice potentials.

JuliaResearch code

No public repository linked

SemiconductorSim.jl

Drift-diffusion simulation of micro/nano semiconductor devices, developed during MS thesis work on high-frequency NEGF-Maxwell co-simulation for the DARPA NanoSim project.

JuliaResearch code

No public repository linked

FDMUtils.jl · PlotPatchGrid.jl

Finite-difference method utilities and patch-grid visualization tools for 2D/3D PDE solvers — structured mesh generation and field plotting for computational physics workflows.

JuliaResearch code

No public repository linked

nvim

Neovim configuration (Lazy.nvim) tuned for Julia scientific computing — LSP, Tree-sitter, tmux integration, and REPL-driven development keymaps.

LuaPublic
View repository ↗

Let's collaborate

Interested in computational physics, scientific machine learning, or high-performance simulation? Reach out to discuss research collaborations and internship opportunities.