Jorge Arce-garro is an Applied Mathematics PhD candidate and Graduate Student Instructor at the University of Michigan with four years of teaching and research experience bridging machine learning, control theory, probability, and quantum information. He combines rigorous mathematical training from Universidad de Costa Rica and UMich with applied work in blockchain and cryptography as a researcher at NethermindEth. Jorge’s research ethos blends theoretical depth—mentored by Prof. Anthony Bloch—with practical systems thinking, enabling contributions that span from probabilistic modeling to quantum-aware algorithms. Based in Ann Arbor, he has a track record of lecturing, curriculum development, and collaborating on interdisciplinary projects that translate abstract theory into real-world cryptographic and distributed-ledger applications.
4 years of coding experience
Master of Science - MS, Applied Mathematics, Master of Science - MS, Applied Mathematics at University of Michigan
Bachelor's degree, Mathematics, Bachelor's degree, Mathematics at Universidad de Costa Rica
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