Pascal Van Hentenryck, A. Russell Chandler III Chair and Professor in the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) at Georgia Tech, director of Tech AI, and director of NSF AI4OPT, was a keynote speaker at AI Festival 2025, held December 1–3 at TU Wien Informatics in Vienna, Austria.

The three-day international festival convened leading researchers, industry experts, and members of the public to explore how artificial intelligence is shaping science, technology, and society. Through keynote talks, panels, and interactive sessions, the event fostered dialogue around emerging AI research, real-world applications, and societal impact.

Van Hentenryck delivered a keynote on “AI for Engineering Optimization” during Day 1: Research, which focused on recent advances in foundational and applied AI. His talk highlighted how AI and optimization methods can be integrated to address complex engineering challenges, with implications for domains such as energy systems, mobility, and large-scale decision-making. 

The session was chaired by Nysret Musliu of TU Wien and the Cluster of Excellence Bilateral AI (BilAI).

The research-focused first day of the festival featured discussions on topics including neurosymbolic AI, large language models, explainable AI, AI in science, and automated problem solving and decision-making. Van Hentenryck’s keynote contributed to these conversations by emphasizing the role of AI-driven optimization in advancing engineering design and operational efficiency.

AI Festival 2025 was co-organized by TU Wien, the Center for Artificial Intelligence and Machine Learning (CAIML), BilAI—funded by the Austrian Science Fund (FWF)—the Vienna Science and Technology Fund (WWTF), and TU Austria. The event underscored the importance of international collaboration across academia and industry in advancing responsible and impactful AI research.

Van Hentenryck’s participation reflects Georgia Tech’s leadership in artificial intelligence, as well as the missions of Tech AI and AI4OPT to advance AI-enabled optimization and decision-making for complex, real-world systems.