Rahul Nadkarni is a Ph.D. candidate in Computer Science & Engineering at the University of Washington with a decade of experience building machine learning systems for science and industry. Trained in EECS and Bioengineering at UC Berkeley, he applies statistical ML and neural language models to problems ranging from neuroimaging time-series to biological sequence modeling and knowledge-base completion. He has industry ML experience from internships at Facebook (Content Integrity) and Google (Maps traffic backend), and a strong background in neural engineering from undergraduate research on brain-machine interfaces. Rahul blends rigorous academic research with practical engineering—often focusing on task adaptation and data augmentation for biological data—bringing both domain intuition and production-aware model development to interdisciplinary teams. An early-career researcher who codes, teaches, and ships ML-driven systems, he’s comfortable moving between signal processing, probabilistic methods, and NLP for scientific discovery.
9 years of coding experience
3 years of employment as a software developer
Bachelor's Degree, Bioengineering, Bachelor's Degree, Bioengineering at University of California, Berkeley
Master of Science - MS, Computer Science & Engineering, Master of Science - MS, Computer Science & Engineering at University of Washington
High School, High School at Monta Vista High School
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