Nicholas Corrado is a PhD student and graduate research assistant at UW–Madison with nine years of experience applying reinforcement learning to real-world robotics and power-systems problems. His research focuses on making RL more data-efficient through adaptive action selection and data augmentation, and he has translated those methods into physical-robotics experiments and Sandia consulting projects. He previously built query execution and storage components for Hustle (an Apache Arrow-based data platform) and designed a robust Lookahead Information Passing variant for dynamic data environments. Nicholas has interned at Amazon on multi-objective LLM alignment and earned recognition at Sandia for impactful contributions to RL projects. Trained in physics, mathematics, and computer science, he blends rigorous modeling instincts from particle-physics experiments with practical systems engineering. Colleagues describe him as someone who moves quickly from theoretical insight to reproducible, production-minded implementations.
9 years of coding experience
4 years of employment as a software developer
Mount Lebanon High School
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at University of Wisconsin-Madison
Bachelor of Philosophy (BPhil), Physics, Bachelor of Philosophy (BPhil), Physics at University of Pittsburgh
Contributions:33 PRs, 51 pushes, 5 branches in 1 month
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