Pascal Van Hentenryck, director of the U.S. National Science Foundation AI Institute for Advances in Optimization (AI4OPT), delivered a keynote at the 11th IFAC Conference on Manufacturing Modelling, Management and Control (MIM 2025) in Trondheim, Norway. His talk, titled AI for Engineering and Societal Impact, explored how the convergence of artificial intelligence, optimization and control can yield solutions that far surpass the capabilities of each technology when applied independently.

Foundations of a Fusion

Van Hentenryck shared key theoretical frameworks that support this integration, including concepts such as primal and dual optimization proxies, predict-then-optimize strategies, self-supervised learning, and deep multi-stage policies. These approaches are designed to enable AI systems to handle complex, real-time decision-making challenges in engineering domains more effectively and responsibly.

Application to Industry Challenges

The keynote emphasized practical applications in areas such as supply chains and manufacturing, aligning closely with the event’s focus on logistics and production systems. The event, hosted by NTNU’s Production Management Research Group and supported by MHI and CICMHE, brought together more than 40 experts for keynotes, breakout sessions, and poster presentations.