I’m a Physics PhD candidate at Louisiana State University, where I build computational models to understand the strange world of quantum materials.
My research lies at the intersection of computational physics and condensed matter theory. I specialize in developing advanced numerical algorithms to simulate complex phenomena in strongly correlated and disordered quantum systems. A core part of my work involves the development and application of quantum embedding theories, such as Dynamical Mean-Field Theory, to probe the non-equilibrium dynamics of these systems. I’m also captivated by the fascinating physics of non-Hermitian quantum phenomena, including the non-Hermitian skin effect. At LSU, I am fortunate to be mentored by Prof. Juana Moreno and Dr. Ka-Ming Tam.
My journey in physics includes a BS-MS Dual Degree from the Indian Institute of Science Education and Research Bhopal. For my MS thesis, I contributed to the LITESOPH project by developing efficient scientific codes to model non-adiabatic dynamics. I’ve also had the privilege of applying my skills in diverse settings, including a summer internship at Los Alamos National Laboratory modeling non-linear light-matter interactions and as a long-term research visitor at Jawaharlal Nehru Center for Advanced Scientific Studies.
When I’m not running simulations, I enjoy playing cricket, table tennis, and chess. I’m an avid chess player on Chess.com (rapid controls are my favorite). Fancy a game? Challenge me: qtinkerer.
I’m always open to discussing physics, new research, or potential collaborations. Feel free to explore my publications, or connect with me on LinkedIn.
Peer Reviewer: Physical Review B, Physical Review A, Chaos
Ph.D. in Physics, 2021 - Present
LSU
BS-MS in Physics, 2020
IISER Bhopal
Demonstrated Unsupervised Domain Adaptation (UDA) from MNIST to MNIST-M using MMD and Domain-Adversarial Neural Networks (DANN) in PyTorch.
Developed a quantitative framework to model the cash flows and price sensitivity of Mortgage-Backed Securities (MBS). The primary focus is investigating the phenomenon of Negative Convexity—the asymmetric risk profile caused by the embedded homeowner prepayment option.
Developed a model to predict the Bee Hive health using localized weather data and a standardized checklist of health indicators.
A Python implementation of Real-Space Dynamical Mean-Field Theory (R-DMFT) designed to handle non-Hermitian Hamiltonians using IPT impurity solver.
Personal research and portfolio website built with Hugo, hosted on GitHub, and automatically deployed via GitHub Pages.
A series of mini-projects implementing Modern Portfolio Theory, volatility modeling, and risk-management strategies using Python and stochastic calculus.