Summary
Pavel Komarov is a research-driven engineer specializing in the mathematics behind signal processing, control theory, and machine learning, with a decade of experience spanning academia, defense, and health-tech. Currently a Graduate Research Assistant at the University of Washington and a PhD candidate in Electrical Engineering, he brings hands-on expertise from roles as Principal Data Scientist and Machine Learning Engineer where he led applied ML, cloud deployments, and study design. He excels at translating deep theoretical insight into elegant, practical solutions—whether building anomaly detection and sensor-fusion systems or simplifying complex data pipelines. Pavel’s background includes teaching at Georgia Tech and production ML work at startups and established firms, reflecting a rare blend of clear pedagogy and production rigor. Outside work he pursues problem-focused curiosity—skiing, climbing, and getting lost in math—which fuels both his creativity and collaborative approach.
10 years of coding experience
Middle Tennessee State University (MTSU)
English, Russian