Subject to: Alain Hertz

2025-12-25 · Source: Subject to · Field: Technology & Digital — Artificial Intelligence & Machine Learning, Data Science & Analytics, Robotics & Autonomous Systems · Depth: Advanced, extended

Summary

This interview features Professor Alan Hertz, a distinguished figure in mathematics and industrial engineering at Polytechnique Montréal, known for his extensive work in combinatorial optimization, graph theory, and algorithmics. Hertz discusses his early life in Sier, Switzerland, his family background, and his passion for music, including playing clarinet and conducting choirs. He recounts his academic journey, highlighting his exceptional performance at EPFL, where he earned a degree in mathematical engineering and won the Domer prize. Key influences include his high school math teacher, Paul Epine, and his PhD supervisor, Dominic de Werra, who guided him into operations research and graph theory. Hertz details his contributions to the taboo search algorithm, his post-doctoral work in Montreal, and his shift from theoretical to practical problem-solving, including projects for Cirque du Soleil and hospital scheduling. He also shares insights into his unique hobby of writing detective novels based on graph theory and his recent groundbreaking discovery in chemistry, identifying only 12 candidate molecules for optimal values regardless of function or size.

Key takeaway

For AI Scientists and Operations Research practitioners, Hertz's career underscores the value of deep theoretical knowledge in solving complex, real-world problems. His work on taboo search, vehicle routing, and the recent chemistry discovery demonstrates that fundamental mathematical insights can lead to highly impactful, efficient solutions. Consider how core theoretical principles in your domain might simplify seemingly intractable problems, even those with millions of variables, by identifying underlying structures that enable polynomial-time solutions.

Key insights

Alan Hertz's career exemplifies the power of foundational mathematical principles applied to diverse real-world challenges.

Principles

• Theoretical understanding informs practical solutions.
• Mentorship is crucial for career trajectory.
• Simplicity can yield profound impact.

Method

Hertz's method involves identifying a graph theory theorem, creating a practical scenario for its application, and then constructing a narrative around it, demonstrating how abstract concepts can solve concrete problems.

In practice

• Apply graph theory to optimize scheduling and network design.
• Utilize resolving sets for efficient recommender systems.
• Explore polyhedral descriptions for chemical structure optimization.

Topics

• Combinatorial Optimization
• Graph Theory
• Tabu Search Algorithms
• Vehicle Routing Problems
• Computational Chemistry

Best for: AI Scientist, Research Scientist, AI Researcher, AI Student

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Editorial summary, takeaway, and curation by AIssential. Original article published by Subject to.