Moncef Chioua

Moncef Chioua, Associate Professor at Polytechnique Montréal, specializes in Chemical Engineering with a focus on process data analysis, machine learning, and control systems for industrial process monitoring and operator support. His work spans pulp and paper, petrochemicals, and energy generation sectors.

Education:

• Ph.D. in Chemical Engineering (Polytechnique Montréal, 2008)
• DEA in Control Systems and Digital Signal Processing (INPL, 2004)
• Engineering Degree in Continuous Process Automation (ESSTIN-INPL, 2003)

Research Interests include fault detection, real-time optimization, and interpretable AI for industrial systems. His recent work applies neural networks and statistical methods to chemical processes, stem cell manufacturing, and metallurgical control.

Publications highlight trends in alarm data analysis, disturbance classification, and hybrid modeling. Notable collaborations include ABB Corporate Research and FP-Innovations.

Scientific Awards:

• Recipient of NSERC Discovery Grant (2021) totaling $3.9 million for research programs

Advising & Grants:

• Supervised Nguyen, B.'s 2024 Master's thesis on interpretable neural networks for fault detection
• Principal Investigator for projects in industrial AI, alarm management, and process optimization

Labs & Teams: Affiliated with the Institute for Data Valorization (IVADO) and previously contributed to ABB's process optimization group (2008-2020) and PAPRICAN's control systems research (2003-2004).