Hsin-Yuan Huang

Hsin-Yuan Huang is an Assistant Professor of Theoretical Physics at the California Institute of Technology and a Staff Research Scientist at Google Quantum AI. His research focuses on building rigorous foundations for understanding how scientists, machines, and future quantum computers can learn and discover new phenomena in the quantum-mechanical universe, including molecules, materials, exotic quantum matter, and engineered quantum devices. He leverages tools from quantum information theory, quantum many-body physics, learning theory, and complexity theory to study when quantum machines can outperform classical systems in learning and prediction, how quantum and physical sciences can be accelerated or automated, and what types of physical phenomena are accessible to classical versus quantum learners. He received his Ph.D. under the supervision of John Preskill and Thomas Vidick, and his doctoral dissertation, *Learning in the Quantum Universe*, was awarded the Milton and Francis Clauser Doctoral Prize for originality and transformative potential. His work aims to develop quantum machines capable of discovering aspects of the universe beyond the reach of classical computation and human intuition.