We are pleased to anounce our next event and the first in our series: Machine Learning Series I. In this talk we will know from 2 industry leaders how they are applying machine learning techniques to produce business results.
It is a great honour to have in our panel Alexandros Kartzoglou, Scientific Director at Telefonica Research, Jose A. Rodriguez-Serrano Data Science Team Lead at BBVA Data & Analytics
Wednesday, May 3rd, 2017 at 19:00 PM (18:45 registration opens)
Alexandros Katzoglou is Scientific Director of Telefonica Research in Barcelona, Spain working on Machine Learning, Deep Learning, Recommender Systems, Information Retrieval. His team includes researchers in the areas of HCI, Networks and Systems. We are creating Machine Learning algorithms for customer data and data generated by Network operations. He received his PhD from the Vienna University of Technology and was a visiting fellow at the Statistical Machine Learning group at NICTA/ANU in Canberra, Australia. He frequently teaches Machine Learning courses at the UPF/GSE with some R, Python, Statistics, Recommender Systems and Deep Learning.
Jose A. Rodriguez-Serrano is currently a Data Science Team Lead at BBVA Data & Analytics since 2015. Formerly, he was Area Manager of the Machine Learning for Services group at Xerox Research Centre Europe, after being a permanent research scientist since 2010 at the Computer Vision Group. Previously he had been a postdoctoral fellow at the University of Leeds and Loughborough University, UK. He obtained his PhD in 2009 from the Universitat Autonoma de Barcelona and a degree in Physics in 2003 from the University of Barcelona. His main research topics have been image retrieval and learning to represent objects through embeddings of generative models and discriminative embeddings. He has published papers in IEEE Trans. PAMI, IJCV, CVPR or ICCV, among others and has 25 patents and patent applications. His main interest has been to apply state-of-the-art machine learning research to solve problems of industrial interest, and is fascinated by the challenge of making research outcomes simple to use for non-experts
This event could not be possible without the collaboration of Mobile World Centre.