Mengyang Gu

Mengyang Gu is an Assistant Professor in the Department of Statistics and Applied Probability at the University of California, Santa Barbara. His research focuses on uncertainty quantification, Gaussian process emulation, statistical calibration, and machine learning for computational science and materials physics. He has developed open-source packages like RobustGaSP, RobustCalibration, and FastGaSP for R and MATLAB.

• Education: PhD in Statistical Science from Duke University (2016)
• Research: Uncertainty Quantification, Gaussian Processes, Materials Science, Dynamical Systems
• Grants: NSF awards for computer model calibration, BioPACIFIC MIP funding
• Awards: Scialog Fellow, Hellman Fellowship, SIAM Early Career Prize, ACM Best Paper
• Students: Mentored PhD graduates including Xubo Liu, Yue He, Hanmo Li, and Xinyi Fang

His group collaborates with materials scientists, physicists, and biologists to develop statistical methods for complex systems. Recent projects include physics-informed ML for polymer phase identification, inverse Kalman filtering, and AI-enabled materials exploration.