Séminaire de Simo Särkkä (Aalto University) Partager ce post

Stochastic Processes in Uncertainty Modeling: Bayesian Filtering and Smoothing

 Date : Sept. 16 2015

 Time : 13:15

 Location : C128 (Barrault)

Abstract This talk is concerned with Bayesian estimation in dynamic systems. In
particular, I will talk about dynamic systems that can be modeled
using differential equations with random input, that is, using
stochastic differential equations (SDEs). In Bayesian point of view
the stochasticity is used to model the uncertainties in the dynamic
system. I will also discuss applications of such models and the
related Bayesian estimation methods – Bayesian filters and smoothers – in fMRI and MEG brain imaging, inverse problems, and target tracking.

Simo Särkkä received his Master of Science (Tech.) degree (with
distinction) in engineering physics and mathematics, and Doctor of
Science (Tech.) degree (with distinction) in electrical and
communications engineering from Helsinki University of Technology,
Espoo, Finland, in 2000 and 2006, respectively. From 2000 to 2010 he
worked with Nokia Ltd., Indagon Ltd., and Nalco Company in various
industrial research projects related to telecommunications,
positioning systems, and industrial process control. From 2010 to 2013
he worked as a Senior Researcher with the Department of Biomedical
Engineering and Computational Science (BECS) at Aalto University,
Finland.

Currently, Dr. Särkkä is an Associate Professor and Academy Research
Fellow with Aalto University, Technical Advisor and Director of
IndoorAtlas Ltd., and an Adjunct Professor with Tampere University of
Technology and Lappeenranta University of Technology. In 2013 he was a
Visiting Professor with the Department of Statistics of Oxford
University and in 2011 he was a Visiting Scholar with the Department
of Engineering at the University of Cambridge, UK. His research
interests are in multi-sensor data processing systems with
applications in location sensing, health technology, machine learning,
inverse problems, and brain imaging. He has authored or coauthored ~60
peer-reviewed scientific articles and has 3 granted patents. His first
book “Bayesian Filtering and Smoothing” was recently published via the
Cambridge University Press. He is a Senior Member of IEEE and serving
as an Associate Editor of IEEE Signal Processing Letters from August
2015.

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