I am a fourth-year PhD candidate in Materials Science at Washington University in St. Louis. My thesis revolves around exploring the interplay of disorder and order in complex materials — from metallic alloys to polar insulators — using density functional theory, thermodynamics, and data science. I develop computational methods, mainly in Python, that combine first-principles calculations with thermodynamic models to predict the stability of complex materials as a function of temperature, composition, strain, etc.

I am currently interested in studying metallic alloys with many components — High Entropy alloys — for their superior mechanical properties. Along with experimental collaborators, I seek to accelerate alloy design with my computational workflows.

On the other hand, I have also studied electrically ordered materials, analogous to magnetic materials, for their application in next-gen memory devices. In particular, I have spent some time on hafnium dioxide, a promising material that can show robust ferroelectricity. I use DFT along with group-theoretical analysis of symmetry to understand the complicated phase diagram of Hafnia as a function of doping, strain, and boundary conditions.

Complementing these lines of research, I have always been interested in Data Science, Machine Learning, and statistical analysis. Since my undergraduate days at the National Institute of Technology Karnataka, I have developed and applied neural networks to various problems ranging from bandgap prediction for solar cells to pneumonia detection in lungs.

My research interests span from Physics to Chemistry to Machine Learning to Materials Science — with a few fields in between 😉. In the future, I hope to solve interesting problems in any field with the help of my interdisciplinary knowledge and skills. I’m always looking out for the next frontier. Check out my research and projects, and reach out if you’d like to talk!

Ciao!


P.S. — If you’d like to know me a bit more, visit my personal website where I share my artistic expressions.