Summary
Alessandro Corbetta is an applied mathematician and Assistant Professor at Eindhoven University of Technology who builds high-reliability, high-performance software to measure and model pedestrian crowd dynamics. He combines large-scale real-life data collection (millions of trajectories) via custom real-time tracking systems—often re-engineered Kinect-based sensors—with stochastic and fluid-dynamics models to study crowd behavior for societal and civil-engineering applications. A daily Python practitioner with experience across C/C++, Matlab, SQL and CI/CD-driven Linux environments, he bridges computer vision, neural networks, HPC and scalable data management to turn complex measurements into predictive models. He holds two PhDs (Applied Mathematics and Structural Engineering) and previously developed parallel simulation code at Los Alamos, reflecting a rare mix of rigorous theory, systems engineering and field deployment.
13 years of coding experience
10 years of employment as a software developer
Doctor of Philosophy (PhD), Computational and Applied Mathematics, Doctor of Philosophy (PhD), Computational and Applied Mathematics at Eindhoven University of Technology
Scientific High School degree, High School/Secondary Diplomas and Certificates, 100/100 cum Laude, Scientific High School degree, High School/Secondary Diplomas and Certificates, 100/100 cum Laude at Liceo scientifico Giordano Bruno
Management of innovation, Management of innovation at Alta Scuola Politecnica
Doctor of Philosophy (PhD), Structural Engineering, Doctor of Philosophy (PhD), Structural Engineering at Politecnico di Torino
Italian, English, French