I'm a theoretical and computational quantum physicist who likes the interface of math, physics and programming. Specifically, I like interfacing machine learning and reinforcement learning techniques with quantum algorithms for solving quantum theory problems as well as designing quantum systems. I'm currently a postdoctoral researcher at JILA, University of Colorado, Boulder.

I usually like working on diverse topics. On the physics side, I work in quantum sensing, quantum computing, quantum information theory, physics informed machine learning, and using reinforcement learning and artificial neural networks to augment quantum algorithms and design tasks (see my Google Scholar )

On the programming side, I love coding hobby projects here and there. I use Python, Mathematica and C++ for work, and Rust for personal projects. My obsession with Rust is a bit recent, and am fascinated about its applicability to scientific computing. In the past, I have also used Fortran, Matlab, Java and R.

My personal website (in progress) can be found here.

• Interpreting convolutional neural networks and using them as a variational quantum algorithm for qubit systems paper
• Using reinforcement learning to optimize design of quantum sensors and circuits Sample Github 1, Sample Github 2
• Using Neural Networks to Solve Hamiltonians Demo