A Great Journey along Industrial Data Science

S. Joe Qin is the Fluor Professor at the Viterbi School of Engineering at the University of Southern California. He is an IEEE Fellow, IFAC Fellow, and AIChE Fellow. Dr. Qin’s research interests include data analytics, machine learning, process monitoring and fault diagnosis, model predictive control, system identification, semiconductor manufacturing and control, building energy optimization, and predictive maintenance and are in parts closely related to the work of Nina Thornhill. He has published over 400 international journal papers, book chapters conference papers and presentations, delivered over 50 invited plenary or keynote speeches and over 120 invited technical seminars worldwide.