Summary
Pavel Zhuravlev is a mathematical statistician and research scientist with a PhD in Chemistry and over a decade of experience blending theoretical biophysics, formal privacy, and applied statistics in both academia and the public sector. Currently at the U.S. Census Bureau, he applies rigorous analytical theory and computational modeling to real-world data problems, leveraging C++, CUDA, Python, and R to build simulation pipelines and reproducible analyses. His background includes developing and validating models for complex biophysical systems like protein folding and organelle dynamics, then translating results into peer-reviewed publications and conference presentations. Known for enjoying open-ended problem solving, he pairs deep quantitative intuition with hands-on software development to move projects from hypothesis to production-ready outcomes. An often-understated strength is his ability to bridge low-level high-performance code with statistical inference workflows, enabling scalable, scientifically grounded solutions.
10 years of coding experience
PhD, Chemistry, PhD, Chemistry at University of North Carolina at Chapel Hill
Lomonosov Moscow State University
Spanish, French, Polish, German, English, Russian