About
Han Yang is a Postdoctoral Scholar in Professor Rowan's research group at the University of Chicago, focusing on interdisciplinary applications of machine learning in scientific domains. He holds a PhD from McGill University and a bachelor's degree in chemistry from the University of Science and Technology of China.
Education
- PhD in Chemistry, McGill University, Montreal, Canada (Supervised by Professor van de Ven)
- Bachelor's Degree in Chemistry, University of Science and Technology of China
Research Interests
Dr. Yang's work bridges machine learning with materials science and computational chemistry. His expertise spans reinforcement learning from natural language feedback, physics-informed neural networks for dynamical systems, and generative models for drug discovery. His doctoral research on nanocellulose materials development informs his current computational approaches to complex scientific problems.
Recent Publications Trends
His 2024-2025 publications reveal a strategic shift toward AI-driven scientific discovery, combining deep learning with domain-specific constraints. Key themes include human-AI collaboration through natural language interfaces, physics-embedded neural architectures for sparse-data systems, and probabilistic generative modeling for pharmaceutical applications—demonstrating exceptional versatility across computer science, chemistry, and engineering disciplines.
Scientific Awards
No scientific awards were mentioned in the provided text.
Advising and Grants
There is no indication of student advising or grant funding in the available information.
Labs and Teams
He actively contributes to the Rowan Group at the University of Chicago, a multidisciplinary research team investigating the convergence of advanced materials, chemical engineering, and artificial intelligence methodologies.
