Gabriele Steidl

Gabriele Steidl received her PhD and habilitation (postdoctoral lecturing qualification) in mathematics from the University of Rostock (Germany). She held a position as an Assistant Professor at the TU Darmstadt (Germany, 1993-1996) and as a Full Professor at the University of Mannheim (Germany, 1996-2010). From 2011 to 2020, she was a Professor at the TU Kaiserslautern (Germany) and a consultant of the Fraunhofer Institute for Industrial Mathematics. Since 2020, she has been a Professor at the Department of Mathematics at the TU Berlin. She worked as a postdoc at the University of Debrecen (Hungary), the University of Zürich and was a Visiting Professor at the ENS Paris/Cachan, the Universitè Paris East Marne-la-Vallèe and the Sorbonne. Since 2020, she has been a member of the “Fachkollegium Mathematik” of the German Research Foundation. She is the Program Director of SIAG-IS (SIAM), on the executive board of the MATH+ Excellence Cluster (Berlin) and serves in the Scientific Advisory Committee of the Helmholtz Association. Starting in 2022, she will be working as Editor-in-Chief of the SIAM Journal of Imaging Sciences. Further, she is a member of the editorial board of the “Journal of Mathematical Imaging and Vision”, the “Journal of Fourier Analysis, Inverse Problems and Imaging” and the “Journal of Optimization Theory and Applications, Numerical Functional Analysis and Optimization, Transactions in Mathematics and its Applications and Acta Applicandae Mathematicae”.

Patrick Pérez

Patrick Pérez received the Ph.D. degree in 1993, for his work on multi-grid Markov random fields. After a postdoc at the Dept of Applied Mathematics of Brown University, he joined Inria in 1994 as a full time researcher, to work on image and video analysis.  From 2000 to 2004, he was with Microsoft Research Cambridge, working on image editing (notably exemplar-based inpainting and Poisson editing) and visual tracking with particle filters. He then returned to Inria as a senior researcher and took, in 2007, the direction of Vista, a research team focusing on video understanding. In 2009, Patrick Pérez joined Technicolor as a Distinguished Scientist, to lead an exploratory research program on computer vision and image analysis, with applications to visual effects and movie post-production.  In 2018, he joined Valeo, a global automotive supplier to create and lead Valeo.ai. This research lab explores in particular the challenges of AI for assisted and autonomous driving: from perception to action, how to train, with limited supervision, multi-sensory models that are accurate, robust, reliable, adaptable, verifiable and interpretable?  

Eero Simoncelli

Eero Simoncelli is Silver Professor at New York University and the Director of the Center for Computational Neuroscience at the Flatiron Institute of the Simons Foundation. Simoncelli received his B.S. in physics (summa cum laude) in 1984 from Harvard University, studied applied mathematics at Cambridge University for a year and a half, and then received his M.S. in 1988 and his Ph.D. in 1993, both in electrical engineering from Massachusetts Institute of Technology. He was an assistant professor of computer and information science at the University of Pennsylvania from 1993 until 1996. He moved to New York University in September 1996, as an assistant professor of Neural Science and Mathematics (later adding psychology, and most recently, data science). Eero received an NSF CAREER award in 1996, an Alfred P. Sloan Research Fellowship in 1998, and was an Investigator of the Howard Hughes Medical Institute from 2000-2020. He was elected a Fellow of the IEEE in 2008, an associate member of the Canadian institute for Advanced Research in 2010, and was elected to the American Academy of Arts and Sciences in 2019. He has received two Outstanding Faculty awards from the NYU GSAS Graduate Student Council (2003/2011), two IEEE Best Journal Article awards (2009/2010) and a Sustained Impact Paper award (2016), an Emmy Award from the Academy of Television Arts and Sciences for a method of measuring the perceptual quality of images (2015), and the Golden Brain Award from the Minerva Foundation, for fundamental contributions to visual neuroscience (2017). His research interests span a wide range of topics in the representation and analysis of visual images, in both machine and biological systems.