Nicholas Mino

My research interests are in quantum machine learning, quantum computing, biological computing, uncertainty quantification, and mathematically grounded machine learning.

My current research at CMU focuses on uncertainty quantification for AI-supported decision-making, particularly certified risk/regret tradeoffs and conformal-style guarantees. Going forward, I hope to explore how these ideas connect to quantum machine learning, quantum algorithms, biological computation, and more general mathematically principled approaches to learning and decision-making under uncertainty.