Malte Kuss
Chief Financial Officer, RWE Americas
PhD Student, Empirical Inference Department (Bernhard Schölkopf), MPI-IS
What is your connection to Tübingen, Malte?
I was a PhD student at the Max Planck Institute for Biological Cybernetics from 2002 to 2006, supervised by Carl Rasmussen. I had studied computer science at TU Berlin and become fascinated by machine learning around the turn of the millennium. Those were the years of the neural winter, before deep learning, so the field worked a lot on kernel methods, boosting, graphical models and statistical learning theory. When I heard that Bernhard Schölkopf was starting a new group in Tübingen, I joined what were the very early days of the Department of Empirical Inference. My thesis focused on Bayesian inference, in particular Gaussian process models.
Is there a memory from your time here that had a lasting positive impact on you?
It was a formative time, and I look back on it very fondly. I learned a great deal, worked hard, had a lot of fun, made lasting friendships and met my wife. What stays with me most from the institute itself is the atmosphere of those early years: a small, very international group of people who were genuinely excited about the same set of ideas, and a close circle of fellow PhD students within it. Beyond the institute, I still remember countless evenings at the fountain on the Marktplatz, games of football and Age of Empires, and mountain bike rides up on the Alb.
The Tübingen training in data analytics, probabilistic reasoning, decision making under uncertainty, and the discipline of asking what a model is actually telling you has proved remarkably transferable, and I draw on it more often than I would have predicted twenty years ago.
Malte Kuss
Where has your career taken you since, and did your time in Tübingen play a role? If so, how?
My career has taken what may look like an unusual route, from Bayesian machine learning research into financing renewable energy growth. Today I am Chief Financial Officer of RWE Americas, where we develop, construct and operate wind, solar and battery storage projects across 27 US states. Interestingly, AI has come full circle and is now central to my professional life again: it is a major driver of the rapidly growing electricity demand in the United States, and at the same time a tool we are introducing into our own finance and operations work. The Tübingen training in data analytics, probabilistic reasoning, decision making under uncertainty, and the discipline of asking what a model is actually telling you has proved remarkably transferable, and I draw on it more often than I would have predicted twenty years ago.