Courses, mentorship, and educational materials in machine learning and reinforcement learning.
Offered as CS 401R at BYU in Fall 2026. A problem-first introduction to RL that starts from a concrete goal and progressively relaxes what you can assume about your data, introducing formalism...
Learn MoreBuilding a research group at BYU around sequential decision making under partial observability, delayed feedback, and irreversibility. Recruiting graduate students whose curiosity, not a fixed agenda, sets the direction.
Learn MoreUndergraduates take on real open questions, not literature summaries — and build new methods with me when a question calls for one.
Learn MoreComprehensive undergraduate introduction to supervised learning, unsupervised learning, and practical ML skills, pairing theory with hands-on implementation of core algorithms.
Learn MoreGraduate-level course on modern RL — offline RL, safe RL, and real-world deployment — bridging theory and practice through implementation projects.
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