Rohan Varma is an AI Scientist with a decade of experience applying machine and deep learning to signal processing, cheminformatics, and molecular machine learning for drug discovery. He holds a Ph.D. in Electrical and Computer Engineering from Carnegie Mellon, where his thesis combined graph signal processing with semi-supervised and active sampling methods for graph-structured data. Rohan has translated research into industry impact through roles at Frontier Medicines and Amazon, and internships at Microsoft and Apple, bridging hands-on engineering with rigorous academic foundations. His technical interests span self-supervised, semi-supervised, and transfer learning as well as computer vision and perception, with a practical bent toward deployment in scientific domains. Trained also in economics and statistics at UC Berkeley, he brings quantitative breadth that informs model design and experimental strategy. Colleagues describe him as someone who thrives at the intersection of theory and application, often surfacing non-obvious structure in complex data.
10 years of coding experience
9 years of employment as a software developer
Bachelor of Arts (B.A.), Economics, Bachelor of Arts (B.A.), Economics at University of California, Berkeley
Master of Science - MS, Electrical and Computer Engineering, Master of Science - MS, Electrical and Computer Engineering at Carnegie Mellon University
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