Curriculum Vitae

Dual PhD, Physics & Computational Mathematics

Research in lattice QCD, quantum field theory, high-performance computing and numerical analysis. Advisor: Prof. Alexei Bazavov.

BS–MS Dual Degree in Physics

Master’s thesis: Numerical modelling of the Casimir effect for fermions on the lattice.

Strong coupling from gradient flow

• Develop high-precision multiscale methods for parameter estimation in stochastic field models.
• Formulate continuous β-function frameworks from gradient-flow evolution.
• Build robust extrapolations with uncertainty control and model-consistent constraints.

Higher-derivative field theories

• Develop scalable C++ simulation and analysis systems for lattice-based models.
• Validate numerical results against analytic benchmarks.
• Generate large ensembles on HPC systems for correlation and propagator measurements.

Machine learning for phase transitions

• Used convolutional networks to identify regime changes in model-agnostic settings.
• Improved predictive performance via histogram reweighting and transfer learning.

Numerical Casimir effect for lattice fermions

• Validated lattice formulations against continuum benchmarks.
• Resolved apparent universality violations through targeted regularisation.

Neural networks for differential equations

Applied physics-informed neural networks to Burgers and Schrödinger equations.

Electromagnetism · Statistical Mechanics · Quantum Mechanics · Quantum Physics · Physics for Life Sciences · Electrodynamics I · Computational Physics · Data Science Capstone

URA Visiting Research Scholar · MSU Graduate School Travel Fellowship · University Distinguished Fellowship · KVPY Fellowship · DST INSPIRE Fellowship · Model Solvay Conference 2020 Winner · DAAD-WISE Finalist