Nikolaos “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 imec 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.

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

He was chair of the EURASIP Technical Area Committee on Signal and Data Analytics for Machine Learning in 2021-2023. He also serves as Associate Editor for the IEEE Transactions on Image Processing. He is a member of the IEEE and EURASIP.

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), sparse signal processing;

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).

• Honorable Mention Award at the 2023 ICCVW and Challenge on Vision and Language Algorithmic Reasoning (VLAR 2023). This relates to methods and datasets for textual explanations for AI models. 
• Best Paper Award at the 2019 IEEE International Conference on Image Processing. The award was given in recognition of an innovative interpretable-by-design deep recurrent neural network model for video processing. 
• Best Paper Award at the 2019 EAI International Conference on Sensor Systems and Software (S-CUBE’19). The award was given in recognition of an innovative method for context-based analysis of urban air quality using an opportunistic mobile sensor network.
• Young Scientist Best Paper Award at the NATO IST-160 Specialist’s Meeting Big Data and AI for Military Decision Making, June 2018. The award was given in recognition of an innovative deep-learning-model that can detect fake news in social media.
• 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 in recognition of the best doctoral thesis to have made an original contribution to informatics or its application (two such award per year in Belgium for all PhDs in informatics).  
• Best Paper Award at the ACM/IEEE International Conference on Distributed Smart Cameras, ICDSC’11, Ghent, Belgium, Aug. 2011.

• 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).