Dr.  Michael Bronstein Digital Library

Based in Lugano, Switzerland
Michael Bronstein


Michael Bronstein is a professor in the Faculty of Informatics at the University of Lugano (USI), Switzerland and a Research Scientist at the Perceptual Computing group, Intel, Israel. He held visiting appointments at Politecnico di Milano (2008), Stanford university (2009), and University of Verona (2010, 2014). Michael got his B.Sc. in Electrical Engineering (2002) and Ph.D. in Computer Science (2007), both from the Technion, Israel. 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. His research appeared in international media and was recognized by numerous awards. In 2012, Michael received the highly-competitive European Research Council (ERC) starting grant. In 2014, he was invited as a Young Scientist to the World Economic Forum New Champions meeting in China, an honor bestowed on forty world's leading scientists under the age of 40. Besides academic work, Michael is actively involved in the industry. He was the co-founder of the Silicon Valley start-up company Novafora, where he served as Vice President of technology (2006-2009), responsible for the development of algorithms for large-scale video analysis. He was one of the principal inventors and technologists at Invision, an Israeli startup developing 3D sensing technology acquired by Intel in 2012 and released under the RealSense brand. 

Available Lectures

To request a single lecture/event, click on the desired lecture and complete the Request Lecture Form.

  • Computational metric geometry
    Many important problems in computer vision and pattern recognition revolve around the notion of "similarity" or "distance". Metric geometry is a branch of theoretical...
  • Geometric deep learning
    In recent years, more and more data science applications have to deal with a somewhat unusual kind of data residing on non-Euclidean geometric domains such as manifolds or graphs. For...
  • Spectral methods for 3D data analysis
    In recent years, geometric data is gaining increasing interest both in the academia and industry. In computer graphics and vision, this interest is owed to the rapid development of 3D acquisition...
  • Start thinking in 3D!
    The last decade has witnessed a series of technological breakthroughs in the acquisition, processing, and analysis of 3D geometric data, enabling applications that are revolutionizing our way of...

To request a tour with this speaker, please complete this online form.

If you are not requesting a tour, click on the desired lecture and complete the Request this Lecture form.

All requests will be sent to ACM headquarters for review.