Daniel Kressner received the Diploma and Ph.D. degrees in mathematics from Technische Universität Chemnitz, Germany, and Technische Universität Berlin, Germany, in 2001 and 2004, respectively. After working at the Universities of Umea, Sweden, and Zagreb, Croatia, as a DFG Emmy Noether PostDoctoral Fellow, he worked as an Assistant Professor at ETH Zurich (2007–2010). Since 2011, he is with the Ecole Polytechnique Fédérale de Lausanne, Switzerland, where he is currently a Full Professor. His research was recognized by a John Todd Award and a SIAM Outstanding Paper Prize (jointly with Christine Tobler).
Daniel Kressner works on numerical linear algebra, covering the whole spectrum of theoretical foundations, algorithmic developments, high-performance parallel computing, and applications. His focus is currently on low-rank matrix and tensor approximation techniques, which play an important role in scientific computing and data science, using techniques from differential geometry, optimization, randomization and algebraic geometry to design and analyze new and highly competitive linear algebra methods.