Anthony Degennaro is a Lead Engineer at GE Aerospace Research with a decade of experience applying machine learning, uncertainty quantification, and high-performance scientific computing to probabilistic design. He holds a Ph.D. in Aerospace Engineering from Princeton and has advanced simulation and statistical expertise developed through roles at Brookhaven and Los Alamos National Laboratories. Anthony combines production-grade software skills in C++, Python, and MPI/OpenMP with modern ML tooling like PyTorch to bridge physics-based PDE modeling and data-driven approaches. His work spans from Gaussian processes and polynomial chaos to Bayesian experimental design and low-dimensional modeling, enabling robust optimization under uncertainty for complex engineering systems. Outside of work he brings a creative edge鈥攎usician, writer, thinker鈥攁nd maintains an active code portfolio and technical blog that reveal both practical code samples and deeper research perspectives.
10 years of coding experience
7 years of employment as a software developer
Bachelor鈥檚 Degree Mechanical/Aerospace Engineering, Bachelor鈥檚 Degree Mechanical/Aerospace Engineering at University of Virginia
Doctor of Philosophy (Ph.D.) Aerospace Aeronautical and Astronautical Engineering, Doctor of Philosophy (Ph.D.) Aerospace Aeronautical and Astronautical Engineering at Princeton University
Contributions:4 commits, 3 PRs, 34 pushes in 7 days
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