Decebal Mocanu
Department
Group
RESEARCH PROFILE
Decebal Mocanu is Associate Professor in Machine Learning within the Department of Computer Science, Faculty of Science, Technology and Medicine at the University of Luxembourg (UL); and Guest Faculty Member within the Data Mining group, Department of Mathematics and Computer Science at the Eindhoven University of Technology (TU/e).
Increases in data and computational power mean Artificial Intelligence (AI) has considerable societal impact. Although impactful, the AI theory is extremely far from creating true intelligence. Thus, the question is not what AI will do to humans, but how humans will improve AI and what they will do with it?
ACADEMIC BACKGROUND
From 2020 until 2023, Decebal was Assistant Professor in Artificial Intelligence and Machine Learning within the DMB group, EEMCS faculty at the University of Twente. In the period 2017 - 2020, Decebal was Assistant Professor in Machine Learning within the Data Mining group, Department of Mathematics and Computer Science, TU/e and a member of TU/e Young Academy of Engineering. Previously, he worked as a PhD candidate at TU/e and as a software developer in industry.
In 2017, Decebal received his PhD in Artificial Intelligence and Network Science from TU/e. During his doctoral studies and after that, Decebal undertook four research visits at the University of Pennsylvania (2014), Julius Maximilians University of Wurzburg (2015), the University of Texas at Austin (2016), and the University of Alberta (2022). Decebal holds a MSc in Artificial Intelligence from Maastricht University for which he received the "Best Master AI Thesis Award", and a BEng in Computer Science from the University Politehnica of Bucharest.
Key Publications
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D.C. Mocanu,E. Mocanu,P. Stone,H.P. Nguyen,M. Gibescu,A. Liotta
Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science
Nature Communications (2018) -
D.C. Mocanu,G. Exarchakos,A. Liotta
Decentralized dynamic understanding of hidden relations in complex networks
Scientific Reports (2018) -
D.C. Mocanu,M. Torres Vega,E. Eaton,P. Stone,A. Liotta
Online contrastive divergence with generative replay: experience replay without storing data
arXiv (2016) -
D.C. Mocanu
On the synergy of network science and artificial intelligence
(2016) -
D.C. Mocanu,H. Bou Ammar,D.J.C. Lowet,K. Driessens,A. Liotta,G. Weiss,K.P. Tuyls
Factored four way conditional restricted Boltzmann machines for activity recognition
Pattern Recognition Letters (2015)
Prizes & Grants
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2017Highly Commended Paper Award - International Journal of Pervasive Computing and CommunicationsElectro-Optical Communication
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2016Travel Award at IJCAI 2016Electro-Optical Communication
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2013Master AI Thesis Award, 1st prize, Maastricht University, the NetherlandsElectro-Optical Communication
Ancillary Activities
No ancillary activities