Rohith Mohanakrishnan is a PhD candidate at UC Berkeley with nine years of multidisciplinary experience at the intersection of computational materials science and data-driven machine learning. He combines first-principles techniques like density functional theory and molecular dynamics with practical ML deployment experience from roles at PayPal, applying models to fraud detection and non-destructive evaluation. Currently researching computational design of liquid electrolytes for Li-ion batteries (Persson Group, Jane Lewis Fellowship), he bridges atomistic insight and scalable data solutions to accelerate materials discovery. An IIT Madras alum with teaching and curriculum experience, he also translates complex science into industry-ready tools and coursework. Notably, his background spans hands-on numerical simulation of plasmonics to production-grade ML pipelines, making him fluent across research, engineering, and education.
9 years of coding experience
2 years of employment as a software developer
Doctor of Philosophy - PhD Materials Science, Doctor of Philosophy - PhD Materials Science at University of California, Berkeley
Indian Institute of Technology Madras
X Science and Maths, X Science and Maths at Velammal Matriculation Higher Secondary School , Mogappair
XI & XII Computer science stream, XI & XII Computer science stream at Maharishi Vidya Mandir,Chetpet
Contributions:4 pushes, 2 branches in 1 year 5 months
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