Xun (Ryan) Huan is an Assistant Professor of Mechanical Engineering at the University of Michigan. Prior to U-M, he was a postdoctoral researcher at Sandia National Laboratories in Livermore, California. His research involves developing computational methods and tools for uncertainty quantification, machine learning, and numerical optimization. He is particularly interested in optimal experimental design, Bayesian analysis, multilevel and multifidelity methods, model misspecification, and scientific computing. Some of his current projects include creating data-driven models for balance training of older adults, and quantifying the uncertainty from deep learning models used in computational medicine.