03 — Research

The Science

Working at the intersection of computational physics and applied mathematics — building numerical solvers, analysing observational data from the universe's most extreme events, and seeking a funded PhD.

01 Research Interests

Where equations
describe things that
actually exist.

I work at the intersection of computational physics and applied mathematics — building numerical solvers, implementing algorithms from scratch, and applying rigorous quantitative methods to real physical problems.

My current focus is astroparticle physics, specifically dark matter direct detection: modelling detector responses, signal-background discrimination, and the statistical inference problems underneath.

I am drawn to problems where computation is the tool that makes the physics legible — where a well-written solver reveals something true about the universe.

90%
BSc Physics · First Class
Miranda House, Delhi
Merit
MSc Applied Mathematics
Imperial College London
PhD
Seeking funded position
Computational Astrophysics
02 Code & Repositories

Codebase

GitHub

Full collection of my computational work — numerical solvers, data pipelines, research implementations.

Python · Numerical Methods · Scientific Computing
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This repository contains the full body of my computational work — from numerical solvers and simulations to data analysis pipelines.

Rather than isolated projects, it reflects a continuous approach to problem-solving in physics: building tools that make complex systems tractable and measurable.

Projects include BSc and MSc thesis work, data-driven astrophysics, and ongoing research. Actively updated.

03 Research Projects
~

Gravitational Waves · LIGO

Gravitational Wave Detection

Data analysis and signal processing with the LIGO detector — searching for ripples in spacetime from the universe's most violent events. Signal-background discrimination and statistical inference.

Interferometry · Bayesian inference · Time-series analysis

Multi-messenger Astrophysics

Neutron Star Collisions

Modelling and analysis of binary neutron star merger events — bridging gravitational wave astronomy with electromagnetic counterparts. One of the most energetic phenomena in the observable universe.

GW astronomy · EM counterparts · Kilonova modelling

Stellar Surveys · Gaia

Gaia Stellar Catalogue

Working with Gaia's billion-star catalogue to explore galactic structure, stellar populations and astrometric precision — one of the richest datasets in the history of astronomy.

Astrometry · Stellar populations · Galactic dynamics

Infrared Astronomy · JWST

James Webb Space Telescope

Analysis of JWST infrared imaging data — probing the early universe, star formation, and galaxy evolution at unprecedented resolution and depth.

Infrared imaging · Early universe · Galaxy morphology
04 MSc Thesis & Technical Work

High-performance solvers
for complex PDE systems.

MSc thesis at Imperial College London — computational modelling using finite element analysis with Firedrake (Python). Implemented multiple discretisation schemes with statistical convergence analysis and rigorous error quantification.

Built a complete FEM library from scratch: matrix assembly, sparse solvers, boundary condition enforcement, nonlinear iteration, and performance benchmarking. Full cycle: physical model → mathematical formulation → numerical implementation → validation.

Coursework spanning Advanced Quantum Mechanics, Dirac Notation, General Relativity, Group Theory, and Advanced Probability — building the theoretical foundation for computational research.

Advanced Probability & Group Theory95%
Computational Quantum Mechanics86%
Numerical ODEs91%
Finite Element Methods76%
Linear Algebra & Tensor Analysis76%

Technical Stack

Python
Firedrake
NumPy / SciPy
MATLAB
SQL · Swift · Git
05 PhD — Next Chapter

Computational
astroparticle physics.

Seeking a funded PhD position in computational astroparticle physics or dark matter detection — ideally based in Germany or the Netherlands. I work independently, build things that work, and am drawn to groups doing rigorous, data-driven science at the frontier.

Dark Matter Detection

Modelling detector responses, signal-background discrimination, statistical inference for direct detection experiments.

Gravitational Wave Astronomy

Multi-messenger astrophysics, compact binary coalescence, data analysis pipelines for next-generation detectors.

Computational Methods

Numerical solvers, machine learning applied to physics, simulation frameworks for astrophysical systems.