Summary
Thomas Draper is a doctoral researcher at Carnegie Mellon University focused on practical, entropy-efficient algorithms for random sampling, bringing four years of interdisciplinary experience across machine learning, quantum computing, and theoretical math. He blends rigorous mathematical foundations—BS work spanning mathematics, physics, computer science, and statistics—with hands-on engineering: implementing diffusion models, compiler inlining heuristics, and Pauli-based circuit optimization during industry internships. His background includes deep theoretical research in logic, computability, and number theory as well as experimental work in quantum physics, giving him a rare ability to move between abstract theory and production-quality systems. Based in Pittsburgh, he gravitates toward problems at the intersection of compositionality, information, and intelligence, and has a demonstrated knack for turning complex formal ideas into practical code.
4 years of coding experience
4 years of employment as a software developer
Montgomery High School
Mountain View High School
Doctor of Philosophy - PhD, Computer Science, Doctor of Philosophy - PhD, Computer Science at Carnegie Mellon University
Bachelor of Science - BS, Mathematics, Physics, Computer Science, and Statistics, Bachelor of Science - BS, Mathematics, Physics, Computer Science, and Statistics at Brigham Young University
German, Spanish, Swedish, Japanese