6 Pancras Square, London N1C 4AG, UK
Email: agyorgy google.com
András György received the M.Sc. (Eng.) degree (with distinction) in technical informatics
from the Technical University of Budapest, in 1999, the M.Sc. (Eng.) degree in
mathematics and engineering from Queen's University, Kingston, ON, Canada,
in 2001, and the Ph.D. degree in technical informatics from the Budapest
University of Technology and Economics in 2003.
He was a Visiting Research Scholar in the Department of Electrical and
Computer Engineering, University of California, San Diego, USA, in spring of
1998. In 2002-2011 he was with the Computer and Automation Research Institute of the Hungarian Academy
of Sciences, where, from 2006, he was a Senior Researcher and Head of the Machine Learning
Research Group. In 2003-2004 he was also a NATO Science Fellow in the
Department of Mathematics and Statistics, Queen's University. He also held a part-time research position at GusGus Capital Llc., Budapest, Hungary, in 2006-2011.
In 2012-2015, he was a researcher in the Department of Computing Science, University of Alberta, Edmonton, AB, Canada. In 2015-2019, he was a Senior Lecturer at the Department of Electrical and Electronic Engineering of Imperial College London, London, UK. Since 2018, he has been a Research Scientist at Deepmind, London, UK.
His research interests include machine learning, statistical learning theory, online learning, adaptive systems, information theory, and optimization.
Dr. György received a best paper award at the 7th IEEE Global Conference on Signal and Information Processing (GLOBALSIP2019) in 2019, the Gyula Farkas prize of the János Bolyai
Mathematical Society in 2001 and the Academic Golden Ring of the
President of the Hungarian Republic in 2003.