Michael Bronstein, University of Lugano, Switzerland

Michael Bronstein received his PhD (with distinction) in Computer Science from the Technion in 2007. Since 2010, he is associate professor of Informatics at the University of Lugano (USI), Switzerland, where he leads a research group on geometric and visual computing. Since 2012, he also serves as research scientist and principal engineer for Perceptual Computing at Intel. Since 2016, he is appointed as associate professor of Applied Mathematics at Tel Aviv University in Israel. He also held visiting appointments at Politecnico di Milano (2008), Stanford university (2009), INRIA (2009), Technion (2013, 2014), University of Verona (2010, 2014), and Tel Aviv University (2015). 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. Most recently, he is interested in deep learning on non-Euclidean structured data such as graphs and manifolds.


Jonathan Manton, University of Melbourne. Australia

Professor Jonathan Manton received his Bachelor of Science (mathematics) and Bachelor of Engineering (electrical) degrees in 1995 and his Ph.D. degree in 1998, all from the University of Melbourne, Australia. From 1998 to 2004, he was with the Department of Electrical and Electronic Engineering at the University of Melbourne. During that time, he held a Postdoctoral Research Fellowship then subsequently a Queen Elizabeth II Fellowship, both from the Australian Research Council.  In 2005 he became a full Professor in the Department of Information Engineering, Research School of Information Sciences and Engineering (RSISE) at the Australian National University. From July 2006 till May 2008, he was on secondment to the Australian Research Council as Executive Director, Mathematics, Information and Communication Sciences. Professor Jonathan Manton’s traditional research interests range from pure mathematics (e.g. commutative algebra, algebraic geometry, differential geometry) to engineering (e.g. signal processing, wireless communications). Recently though, led by a desire to participate in the convergence of the life sciences and the mathematical sciences, he has started to apply his expertise to research in neuroscience. Professor Jonathan Manton also has extensive experience in software development.


Thomas Fletcher, University of Utah, USA

Tom Fletcher is Associate Professor in the School of Computing, University of Utah, and works within the Scientific Computing and Imaging Institute. He received his B.A. degree in Mathematics at the University of Virginia in 1999. He received an M.S. in Computer Science in 2002 followed by a Ph.D. in Computer Science in 2004 from the University of North Carolina at Chapel Hill. Dr. Fletcher’s research is focused on creating novel methods at the intersection of statistics, mathematics, and computer science to solve problems in medical image analysis. He is currently collaborating with researchers in Autism and Alzheimer’s disease at the University of Utah on the statistical analysis of combined imaging modalities, including structural MRI, DTI, fMRI and PET in longitudinal studies.


Marc Niethammer, University of North Carolina, Chapel Hill, USA

Marc Niethammer is a Professor in the Department of Computer Science, at the University of North Carolina, Chapel Hill with a joint appointment in the Biomedical Research Imaging Center (BRIC). His research interests lie in the areas of biomedical image analysis.  His work has ranged from approaches for image segmentation, to shape analysis, to deformable image registration and regression. Most recently he has focused on fast approximate approaches. He is particularly interested in the interplay between disciplines, where theory drives applications and applications influence theory development. His current application areas are brain imaging, osteoarthritis, pediatric airway diseases, and cancer.



Stefano Soatto, University of California, Los Angeles, USA

Professor Soatto received his Ph.D. in Control and Dynamical Systems from the California Institute of Technology in 1996; he joined UCLA in 2000 after being Assistant and then Associate Professor of Electrical and Biomedical Engineering at Washington University, and Research Associate in Applied Sciences at Harvard University. Between 1995 and 1998 he was also Ricercatore in the Department of Mathematics and Computer Science at the University of Udine – Italy. He received his D.Ing. degree (highest honors) from the University of Padova- Italy in 1992.His general research interests are in Computer Vision and Nonlinear Estimation and Control Theory. In particular, he is interested in ways for computers to use sensory information (e.g. vision, sound, touch) to interact with humans and the environment.Dr. Soatto is the recipient of the David Marr Prize (with Y. Ma, J. Kosecka and S. Sastry of U.C. Berkeley) for work on Euclidean reconstruction and reprojection up to subgroups. He also received the Siemens Prize with the Outstanding Paper Award from the IEEE Computer Society for his work on optimal structure from motion (with R. Brockett of Harvard). He received the National Science Foundation Career Award and the Okawa Foundation Grant. He is Associate Editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence (PAMI) and a Member of the Editorial Board of the International Journal of Computer Vision (IJCV) and Foundations and Trends in Computer Graphics and Vision.