Michael Bronstein (Institute of Computational Science, University of Lugano (USI), Switzerland / PerceptualComputing Gro up, Intel)
Thursday, 9.1.2014, 12:30
Spectral methods proved to be an important and versatile tool in a wide range of problems in the fields of computer graphics, machine learning, pattern recognition, and computer vision, where many important problems boil down to constructing a Laplacian operator and finding a few of its eigenvalues and eigenfunctions (classical examples include diffusion distances, diffusion maps, and spectral clustering).
In this talk, I will show how to generalize spectral geometry to settings where one has multiple data spaces. Our construction of "multimodal" spectral geometry is based on the idea of simultaneous diagonalization of Laplacian operators. I will show how this problem is related to the problem of finding closest commuting operators, and discuss efficient numerical methods for its solution. As examples of applications, I will show problems from the domain of 3D shape analysis, computer vision, pattern recognition, and image processing.
Michael Bronstein received the Ph.D. with distinction from the Department of Computer Science, Technion in 2007. In 2010, he joined the Institute of Computational Science in the Faculty of Informatics at the University of Lugano (USI), Switzerland. Prior to joining USI, Michael held a visiting appointment at Stanford university. His main research interests are theoretical and computational methods in spectral and metric geometry and their application to problems in computer vision, pattern recognition, shape analysis, computer graphics, image processing, and machine learning.
Michael has authored over 70 publications in leading journals and conferences, over 20 patents, and the book "Numerical geometry of non-rigid shapes" (Springer, 2008). Highlights of his research were featured in CNN, SIAM News, and Wired. His research was recognized by numerous awards, including the Kasher prize (2002), Thomas Schwartz award (2002), Hershel Rich Technion Innovation award (2003), the Copper Mountain Conference on Multigrid Methods Best Paper award (2005), the Adams Fellowship (2005), and the EUROGRAPHICS Service Award (2012). In 2012, he won the highly competitive ERC Starting Grant.
Besides academic work, Michael is actively involved in industrial applications, technology transfer, and consulting to technological companies. His track record includes developing and licensing algorithms for large-scale video analysis applications at the Silicon Valley start-up company Novafora (2004-2009 as co-founder and VP of video technology) and developing coded-light 3D camera based on his patents at the Israeli start-up Invision (2009-2012 as one of the principal technologists). Following the multi-million acquisition of Invision by Intel in 2012, Prof. Bronstein currently also serves as Research Scientist at Inte