Summary
Takumi Matsuzawa is a postdoctoral researcher at Cornell University combining experimental physics, data science, and machine learning to explore biomolecular condensates and liquid-liquid phase separation. He previously engineered a high-speed, multi-camera data acquisition system and built a Python library of over 20,000 lines to analyze 3D/4D flow, dramatically reducing TB-scale data to actionable insights. His work spans turbulence analysis, optical-flow estimation for particle image velocimetry, and CNN-based velocity inference, with a track record of mentoring students and publishing on neural-network models of synaptic plasticity. He earned a BA in Physics and Chemistry from Kalamazoo College (summa cum laude) and a PhD/MS in Physics from the University of Chicago, with prior roles including research and teaching assistantships. Based in Ithaca, New York, he maintains an active open-science profile and a personal site highlighting ongoing research, including turbulence work that was highlighted on a Nature Physics cover.
8 years of coding experience
8 years of employment as a software developer
Bachelor of Arts (B.A.), Physics and Chemistry, Summa cum laude, 4.0/4.0, Bachelor of Arts (B.A.), Physics and Chemistry, Summa cum laude, 4.0/4.0 at Kalamazoo College
Doctor of Philosophy - PhD, Physics, Doctor of Philosophy - PhD, Physics at University of Chicago
Master of Science - MS, Physics, Master of Science - MS, Physics at The University of Chicago
English, Japanese, German