Summary
Kyle Poore is a University of Miami-trained computer scientist and teaching assistant with 12 years of experience supporting undergraduate and graduate courses in programming, systems, and cryptography. He pairs hands-on instructional work—tutoring, grading, and lecturing—with research in distributed reinforcement learning, exploring efficient communication between independent exploratory agents for robotics and AI. His academic and research roles include configuring and evaluating automated theorem provers, reflecting a comfort with formal methods alongside applied systems work. Based in Florida, he brings deep institutional knowledge of curriculum and student mentorship while continuing to push toward scalable multi-agent learning. Colleagues know him for translating complex research problems into teachable components and for blending practical systems skills with theoretical rigor.
12 years of coding experience
2 years of employment as a software developer
Master's Degree, Computer Science, Master's Degree, Computer Science at University of Miami
English, Spanish