Summary
Konstantin Zuev is a teaching professor in Computing and Mathematical Sciences at Caltech with nine years of focused academic and research experience and a longer trajectory in applied mathematics and uncertainty quantification. He combines deep theoretical training (PhD in Mathematics from MSU and PhD-level work in civil engineering at HKUST) with extensive teaching and research roles across top institutions, including USC, Liverpool, Northeastern, and multiple Caltech appointments. His work bridges rigorous mathematics, data-driven modeling, and practical visualization/analytics, evidenced by long-term collaborations with Virtualitics where he serves on the Scientific Advisory Board. Based in Pasadena, he’s known for translating complex probabilistic and network-theoretic ideas into teachable curricula and industry-applicable tools, bringing a rare mix of frontline pedagogy and advisory impact. An observer might note his career rhythm alternating between deep research fellowships and hands-on teaching roles, signaling strength in both discovery and mentorship.
9 years of coding experience
3 years of employment as a software developer
Hong Kong University of Science and Technology (HKUST)
Lomonosov Moscow State University
English, Russian