Soumaya Yacout

Soumaya Yacout is a Full Professor in the Department of Mathematical and Industrial Engineering at Polytechnique Montréal. She holds a Doctorate in Science from George Washington University and has been a leading academic in industrial engineering and artificial intelligence for over two decades.

Her research focuses on Industry 4.0, predictive maintenance, and data-driven decision-making. Key projects include the Intelligent Cyber-Physical Systems Lab, developing cyber-physical platforms for Industry 4.0 factories, and creating algorithms for big data analysis in manufacturing systems. She also leads the CĒOS Net network, advancing smart maintenance strategies for heavy-duty electrical buses.

Yacout has supervised over 27 PhD and Master’s students, with notable alumni contributing to sectors like aerospace, automotive, and smart manufacturing. Her work integrates AI, optimization, and machine learning to address complex industrial challenges, including fault diagnosis, prognosis, and real-time decision-making systems.

Her recent publications emphasize AI applications in maintenance, digital twins, and predictive modeling. She leads interdisciplinary teams and collaborates with industry partners on projects funded by IVADO and NSERC, driving innovation in sustainable manufacturing and smart infrastructure.