Benjamin Doerr is a full professor at the French Ecole Polytechnique. He received his diploma (1998), PhD (2000) and habilitation (2005) in mathematics from Kiel University. His research area is the theory of both problem-specific algorithms and randomized search heuristics like evolutionary algorithms. Major contributions to the latter include runtime analyses for existing evolutionary algorithms, the determination of optimal parameter values, and complexity theoretic results. Benjamin's recent focus is the theory-guided design of novel operators, on-the-fly parameter choices, and whole new evolutionary algorithms, hoping that theory not only explains, but also develops evolutionary computation.

Together with Frank Neumann and Ingo Wegener, Benjamin Doerr founded the theory track at GECCO and served as its co-chair 2007-2009, 2014, and 2023. He is a member of the editorial boards of "Artificial Intelligence", "Evolutionary Computation", "Natural Computing", "Theoretical Computer Science", and three journals on classic algorithms theory. Together with Anne Auger, he edited the the first book focused on theoretical aspects of evolutionary computation ("Theory of Randomized Search Heuristics", World Scientific 2011). Together with Frank Neumann, he is an editor of the recent book "Theory of Evolutionary Computation - Recent Developments in Discrete Optimization" (Springer 2020).