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Nikos Deligiannis is an associate professor (hoofdocent) at the Department of Electronics and Informatics (ETRO) at Vrije Universiteit Brussel (VUB) and a senior scientist at the imec research institute in Belgium. He is also the Programme Director of the Master in Applied Computer Science at VUB. 

In 2006, he received the Diploma in electrical and computer engineering from the University of Patras in Greece and, in 2012, the Ph.D. degree (Hons.) in engineering sciences from Vrije Universiteit Brussel in Belgium. From 2013 to 2015, he was a senior researcher at the Department of Electronic and Electrical Engineering at University College London, UK.

"We have to understand in depth a technology before applying it."

His current research interests focus on interpretable machine learning, signal processing, and distributed learning for computer vision, data mining, and natural language processing. He has authored over 130 journal and conference publications, 5 book chapters, and 5 international patent applications. Here are his Google ScholarORCIDScopus, and dblp profiles. 

Since 2021, he serves as chair of the EURASIP Technical Area Committee on Signal and Data Analytics for Machine Learning. He also serves as Associate Editor for the IEEE Transactions on Image Processing. He is a member of the IEEE and EURASIP.

Research Interests 

Nikos and his team conduct fundamental and applied research in

Machine learning and signal processing, focusing on theory and architectures for Explainable AI (interpretable convolutional neural networks, recurrent neural networks and deep multimodal networks), compressed sensing, sparse coding, robust principal component analysis, and matrix factorization;

Big data sensing, processing, and analysis, addressing applications in social media data analytics (e.g., Fake news detection), smart city data analytics (hyperlocal air-pollution estimation, traffic event detection);

Multimodal visual computing, focusing on the processing and analysis of diverse imaging modalities with various applications from entertainment and surveillance to non-destructive testing;

Natural language processing (fact verification and automated clinical coding).

Achievements (Honors & Awards) 
  • Best Paper Award at the 2019 IEEE International Conference on Image Processing. The award was given in recognition of an innovative explainable deep recurrent neural network model for video data processing and analysis. [top 0.3% paper] 
  • Young Scientist Best Paper Award at the NATO IST-160 Specialist’s Meeting Big Data and AI, Bordeaux, France, June 2018. The award was given in recognition of an innovative deep learning model that can detect fake news in social media and geolocate users
  • 2017 EURASIP Best PhD Award in recognition of the EURASIP doctoral thesis with the highest impact in terms of publications and citations in the period 2012-2017.
  • 2013 Scientific Prize FWO-IBM Belgium for Informatics in recognition of the best doctoral thesis to have made an original contribution to informatics or its application.
  • Best Paper Award at the International Conference on Distributed Smart Cameras, ICDSC’11, Ghent, Belgium.
Memberships 
  • Associate Editor for the IEEE Transactions on Image Processing, April 2021-April 2024 (T-IP is the flagship IEEE publication in image processing).
  • Chair of the EURASIP Technical Area Committee on “Signal and Data Analytics for Machine Learning”, January 2021 – December2023.
  • Vice-Chair of the EURASIP Technical Area Committee on “Signal and Data Analytics for Machine Learning”, January 2018 – December 2020.
  • Member of the Instritute of Electrical and Electronics Engineers (IEEE).
  • Member of European Association for Signal Processing (EURASIP).