Hitarth Choubisa is a machine learning specialist and research scientist with 9 years of experience applying ML, quantum chemistry, and quantum computing to accelerate materials discovery and energy applications. As a founding-team researcher at Orbital Materials and currently at Xanadu, he builds prediction-to-demonstration pipelines that are tightly grounded in experiment, translating cutting-edge theory into practical materials solutions. His PhD from the University of Toronto yielded high-impact publications and over $1M in grant funding, and he has taught industry-focused ML bootcamps for chemists and engineers. Earlier roles at Sony and Total involved deploying ML for battery state-of-charge estimation and developing error-correction schemes for photonic quantum simulators, reflecting a rare blend of device-level engineering and advanced algorithm development. He is driven by tooling that speeds scientific discovery and often bridges academic rigor with deployable ML systems for energy materials.
9 years of coding experience
2 years of employment as a software developer
Indian Institute of Technology Bombay
Doctor of Philosophy - PhD Electrical and Computer Engineering, Doctor of Philosophy - PhD Electrical and Computer Engineering at University of Toronto
High School Maths Science stream, High School Maths Science stream at Nalanda Academy
Secondary Certificate Examination, Secondary Certificate Examination at Modern School
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Hitarth Choubisa - Machine Learning Specialist at Xanadu