“I don't lie to my students. I tell them it won't be easy.”

When the holiday season rolls around every year, many single students wonder who they’ll take with them to their traditional family dinner. The topic of Daniel Kuhn’s last class of the year couldn’t come at a better time: he usually devotes this class to the “marriage problem,” a systematic strategy for finding the optimal partner. Kuhn, who was named the best teacher in the management of technology and entrepreneurship section for 2023, routinely uses left-of-field examples and analogies like this to explain key concepts in risk analysis and optimization – and to etch them in students’ memories. For instance, he performs a magic trick, whereby he reads the mind of a student who has randomly picked a card from a poker deck, to illustrate the law of large numbers for Markov chains.

Does Kuhn, who holds degrees in theoretical physics and economics, see this approach as a way to make complex subjects easier to digest? “What I can say for certain is that I don’t lie to my students: I lay my cards on the table at the start of the semester and warn them that it won’t be easy,” he says. His way of keeping the young men and women who attend his classes engaged is to explain “how all the theory we study, no matter how grueling it may be, has real-world applications.” Kuhn also leaves “plenty of room for practical exercises” where students work on intriguing challenges such as how to stabilize an aircraft engine or how to optimize the use of gamma rays to destroy tumor cells without simultaneously killing healthy cells. “I feel lucky to be making a living from teaching what I love and find most interesting,” he says. “I’m naturally very enthusiastic in the classroom. Perhaps that sweetens the pill for my students – to the extent that they might even enjoy coming to class.”

Kuhn was a faculty member at Imperial College London before joining EPFL in 2013. He knows all too well that if he wants his students to work hard, he has to work hard for them, too: “I’m upfront with my students. I look them in the eye and tell them I’m there for them. And I encourage feedback.” Kuhn admits he found it hard to teach classes online during the pandemic: “So many students had their cameras and microphones turned off. The lack of contact was demoralizing.” He’s equally dismayed by the fact that, since the pandemic, many students are choosing not to attend classes in person, “especially those who are struggling.” Luckily for Kuhn, who serves as Professor of Operations Research at EPFL, his hard work hasn’t gone unnoticed: his Master’s class entitled Optimal Decision Making received 100% positive feedback from students for two years in a row.

Learning for enjoyment rather than by rote

When asked about the most important value he tries to convey through his teaching, Kuhn is unequivocal: “Clarity of thought! Optimization is a mathematical discipline based on theorems and proofs. My students may be engineering and management majors, but the only way to really achieve clarity of thought is to instill in them the theoretical foundations of the discipline without compromising on rigor and complexity.” That’s why it’s so important to strike the right balance between theory and practice – so that students aren’t put off but instead come to appreciate the joys of mathematics.

“I’ve loved math for as long as I can remember,” says Kuhn, who holds the EPFL Chair of Risk Analytics and Optimization (RAO) and wrote his PhD thesis on operations research. He explains that his interest in physics developed gradually over the years “through contact with physicists in my circle.” When he later discovered computer science, he realized that “combining these areas of interest might prove useful to me in life.” Kuhn adds: “The idea of learning something for the pleasure of it is what I try to pass on to my students. It’s much easier – and more effective – to apply knowledge when you enjoy and understand it than when you’ve simply learned something by rote.”

With and without a computer

Kuhn also has plenty of opportunities to indulge his passion for his subject outside of the classroom: “My current research interests are focused on data-driven optimization and the development of efficient computational methods for the solution of stochastic optimization problems [problems involving sequences of random variables].” He’s also taking part in a project for Swissgrid, Switzerland’s national grid operator, that aims to use drones and other technology to optimize the grid inspection process. In this case, the problem is bounded by two constraints: Swissgrid must be able to be reach any part of the country in less than 30 minutes, and as few drones must be purchased as possible.

Doesn’t Kuhn find this kind of work mentally taxing? “Knowing how to frame an optimization problem in concrete terms and then creating an algorithm that can solve it is exactly what my discipline is all about. I’m also the kind of person who enjoys problem-solving in my spare time – even if I don’t have a computer to help me!”