- Tenure track positions in the Mathematics and Statistic Department at UNSW
- RMITOpt Seminar – August the 17th: Dr Lizhen Shao, University of Science and Technology Beijing, China
|Speaker: Dr Simon Williams, Senior Fellow in Dynamical Systems, at the University of Melbourne
Title: The Information Geometry of Sensing
Date and Time: Friday, August 3rd, 3.00pm – 4.00pm
Location: Building 8 Level 9 Room 66 (AGR) RMIT City campus (To connect via visimeet please contact firstname.lastname@example.org)
|Abstract: Information Geometry is the application of differential geometry to statistical estimation allowing parameters to take values on a manifold. The main results have been limited to one dimension and even then the curves have been embedded in a surrounding flat space. In this talk I will outline an application of information geometry to statistical signal processing of sensors that exercises higher dimensional manifolds intrinsically. Here the problem is to estimate the parameters of a target from the noisy measurements of a sensor. Not only can we describe how the information derived by the sensor behaves as the target moves, but we can also see how that varies as we change the parameters of the sensor too. This opens up a whole new area of analysis where target and sensor compete for the information available. This is joint work with Prof Bill Moran and Arthur Suvorov.
Bio: Simon was born in Germany while his father was on sabbatical there, but grew up in Melbourne and then Adelaide, where did his undergraduate studies in Mathematical Physics and Pure Mathematics. I went to Oxford to do graduate study with Roger Penrose on general relativity and conformal field theory (although both of these reduce to differential equations if you stare at them hard enough!) Since returning to Australia he has lectured at Adelaide University, worked as a radar signal processor at DSTO, a grammatical model builder at CSIRO, and lectured again, much better, at Flinders University before moving to Melbourne to work with Prof Bill Moran on pure and applied signal processing.