Xinfan Lin

Dynamic system modeling, diagnostics, and control; machine learning and data analytics; control-integrated design and optimization; automotive, energy and aerospace applications

Professor Lin’s research lies at the intersection of system dynamics and control, data science and design optimization. His group combines multi-physical domain knowledge, control theories and emerging machine learning and data analytics to model, design, control and diagnose dynamic systems. Current interests and applications include intelligent battery management systems, electric vehicles, unmanned aerial systems (UAS), electric-vertical-takeoff and landing (eVTOL) aircraft and spacecraft, among others. These efforts will contribute to the revolution of transportation and the logistics network of human society.