Jinsong Pei

Dr. Pei’s research interests are multidisciplinary, centering on modeling nonlinear dynamical systems using real world data measurements. Her passion, experience, and expertise reside in the application of advanced computational and scientific machine learning methods for modeling and simulation toward addressing the societal grand challenges of infrastructure renewal, climate change mitigation and adaptation, and building sustainable and resilient environments. The broad utility of her work is in structural, mechanical, aerospace, and biomechanical engineering to enable damage detection, damage prognosis, control, digital twins, and more. Dr. Pei’s team studies the mechanical counterparts of memristors, memcapacitors, and more, which form a new family of hysteresis models, called mem-models, with new physical insights and improved computational efficiency. Besides mem-models, Dr. Pei has made a novel contribution to interpretable machine learning for nonlinear function approximation.