Speaker: Ercan Engin Kuruoğlu, Institute of Science and Technology of Information-CNR

Title:  Bayesian Data Analysis Tutorial

Date/Time: 6 February, 2020  /  10.40-12.30

Place: FENS L035

Abstract: Bayesian Theory, so simple, so understated yet so influential in today's science and technology continues to affect how we live our lives increasingly even when we are not aware of it. This tutorial will start with the philosophy and history of the Bayesian theory and will present numerical Bayesian methods including Markov chain Monte Carlo, Reversible Jump MCMC, particle filtering. It will underline some of the current research issues and hot applications.

Bio: Ercan Engin Kuruoglu received his BSc and MSc degrees in Electrical and  Electronics Engineering from Bilkent University MPhil and PhD degrees in Information Engineering from the University of Cambridge, Cambridge, United Kingdom, in 1995 and 1998, respectively. In 1998, he joined Xerox Research Center Europe, Cambridge. He was an ERCIM fellow in 2000 with INRIA-Sophia Antipolis, France. In January 2002, he joined the Institute of Science and Technology of Information-CNR (Italian National Council of Research) , Pisa, Italy. He was a visiting professor for periods of 1-3 months with Georgia Tech-China in 2007, 2011 and 2016, Humboldt University in Berlin in 2012, Southern University of Science and Technology of China, Shenzhen in 2017, University of South Australia in 2018-2019 and Zhejiang Gongshang University, Hangzhou in 2019. He is currently a Visiting Professor at Tsinghua-Berkeley Shenzhen Institute, on sabbatical leave from ISTI-CNR where he holds a Chief Scientist (Dirigente di Ricerca) position. He was an associate editor for the IEEE Transactions on Signal Processing and IEEE Transactions on Image Processing. He is currently the editor in chief of Digital Signal Processing: A Review Journal. He acted as a technical co-chair for EUSIPCO 2006 and a tutorials co-chair of ICASSP 2014. He is a member of the IEEE Technical Committees on Signal Processing Theory and Methods, Machine Learning for Signal Processing and Image, Vision and Multidimensional Signal Processing. He was a plenary speaker at DAC  (Data Analysis for Cosmology) 2007, ISSPA (Int. Symposium on Signal Processing and Analysis) 2010, IEEE SIU (Sinyal Isleme ve Uygulamalari) 2017, Entropy 2018, TBSI-WODS  (Workshop on Data Science) 2019 and tutorial speaker at IEEE ICSPCC  (Int. Conf. Signal Processing, Communications and Computing) 2012. He was a Chinese Government 111 Project Foreign Expert 2007-2011. He was an Alexander von Humboldt Experienced Research Fellow in the Max Planck Institute for Molecular Genetics in 2013-2015. His research interests are in the areas of statistical signal and image processing and information and coding theory with applications in computational biology, remote sensing, telecommunications, earth sciences and astrophysics.

Contact: Ersin Göğüş