Summary
Dennis Yatunin is a Research Software Engineer based in New York with 11 years of experience applying mathematics, statistics, and machine learning to challenging problems in physics, biology, and astronomy. At Caltech he builds reproducible pipelines and numerical solvers—bridging Fortran/Mathematica legacy code with modern ML stacks like TensorFlow and Jupyter to turn heterogeneous scientific data into actionable results. His work includes reconstructing galaxy spectra from photometry, simulating planetary hailstone formation using GCMs, and modeling enzyme proofreading, showcasing a rare blend of theoretical insight and production-oriented software engineering. Comfortable across databases, numerical analysis, and statistical modeling, he brings rigorous academic training in CS and physics to pragmatic, well-documented research software that accelerates discovery.
11 years of coding experience
1 year of employment as a software developer
California Institute of Technology