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Nicolai Petkov
Nicolai Petkov (born 1956) is professor of Intelligent Systems and computer science at the University of Groningen, known for his contributions in the field of brain-inspired computing, pattern recognition, machine learning, and parallel computing.
== Life and work ==
Petkov received his doctoral degree at the Technische Universitaet Dresden in Germany. After graduation he worked at several universities and in 1991 he was appointed Professor of Computer Science (chair of Intelligent Systems and Parallel Computing) at the University of Groningen. He was PhD thesis director (promotor) of Michael Wilkinson (1995), Henk Bekker (1996), Marc Lankhorst (1996), Frank Schnorrenberg (1998), Thomas A. Lippert (1998), Peter Kruizinga (1999), Michel Westenberg (2001), Simona E. Grigorescu (2003), Cosmin Grigorescu (2004), Anarta Ghosh (2007), Gisela Klette (2007), Lidia Sanchez Gonzalez (2007), Erik Urbach (2008), Easwar Subramanian (2008), Giuseppe Papari (2009), Georgeos Ouzounis (2009), Florence Tushabe (2010), Panchalee Sukjit (2011), George Azzopardi (2013), Ioannis E. Giotis (2013), Fred N. Kiwanuka (2013), Ando C. Emerencia (2014).〔(Nicolai Petkov ) at Mathematics Genealogy Project.〕 At the University of Groningen he was scientific director of the Institute for Mathematics and Computer Science (now Johann Bernoulli Institute) from 1998 to 2009, and he is member of the University Council and chairman of the Science Faction since 2011.
Petkov is associate editor of several scientific journals. He co-organised and co-chaired the 10th International Conference of Computer Analysis of Images and Patterns CAIP 2003 in Groningen, the 13th CAIP 2009 in Münster, Germany, the 16th CAIP 2015 in Valletta, Malta, and the Workshops Braincomp 2013 and 2015 on Brain-Inspired Computing in Cetraro, Italy.
Petkov's initial research in the late 1980s was in the field of systolic parallel algorithms. His current research interests are in the field of development of brain-inspired pattern recognition and machine learning algorithms that he applies to various types of big data: image, video, audio, text, genetic, medical, sensor, financial, web, and heterogeneous.〔(Nicolai Petkov research ) at rug.nl. Accessed 2013.11.05〕 He develops methods for the generation of intelligent programs that are automatically configured using training examples of events and patterns of interest.
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