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Persoonlijk profiel

Quote

"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?"

Research profile

Decebal Mocanu is Assistant Professor in Artificial Intelligence and Machine Learning within the DMB group, Faculty of Electrical Engineering, Mathematics, and Computer Science at University of Twente and Guest Assistant Professor within the Data Mining group, Department of Mathematics and Computer Science at Eindhoven University of Technology. From September 2017 until February 2020, Decebal was Assistant Professor at TU/e, and a member of TU/e Young Academy of Engineering. His short-term research interest is to conceive scalable deep artificial neural network models and their corresponding learning algorithms using principles from network science, evolutionary computing, optimization and neuroscience. Such models shall have sparse and evolutionary connectivity, make use of previous knowledge, and have strong generalization capabilities to be able to learn, and to reason, using few examples in a continuous and adaptive manner.

Most science carried out throughout human evolution uses the traditional reductionism paradigm, which even if it is very successful, still has some limitations. Aristotle wrote in Metaphysics “The whole is more than the sum of its parts”. Inspired by this quote, in long term, Decebal would like to follow the alternative complex systems paradigm and study the synergy between artificial intelligence, neuroscience, and network science for the benefits of science and society.

Academic background

In 2017, Decebal received his PhD in Artificial Intelligence and Network Science from TU/e. During his doctoral studies, Decebal undertook three research visits: the University of Pennsylvania (2014), Julius Maximilian University of Wurzburg (2015), and University of Texas, Austin (2016).

Prior to this, in 2013, he obtained his MSc in Artificial Intelligence from Maastricht University . During his master studies, Decebal also worked as a part time software developer at We Focus BV in Maastricht. In the last year of his master studies, he also worked as an intern at Philips Research in Eindhoven, where he prepared his internship and master thesis projects. Decebal obtained his Licensed Engineer degree from University Politehnica of Bucharest. While in Bucharest, between 2001 and 2010, Decebal started MDC Artdesign SRL (a software house specialized in web development), worked as a computer laboratory assistant at the University Nicolae Titulescu, and as a software engineer at Namedrive LLC.

Affiliated with

For an updated webpgae, please see https://people.utwente.nl/d.c.mocanu

Vingerafdruk Verdiep u in de onderzoeksgebieden waarop Decebal C. Mocanu actief is. Deze onderwerplabels komen uit het werk van deze persoon. Samen vormen ze een unieke vingerafdruk.

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Projecten

Interoperability of Heterogeneous IoT Platforms

Exarchakos, G., Mocanu, D. C., van der Lee, T. & Exarchakos, G.

1/01/1631/12/18

Project: Onderzoek direct

Onderzoeksoutput

Scalable training of artificial neural networks with adaptive sparse connectivity inspired by network science

Mocanu, D. C., Mocanu, E., Stone, P., Nguyen, H. P., Gibescu, M. & Liotta, A., 19 jun 2018, In : Nature Communications. 9, 1, 12 blz., 2383.

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

Open Access
Bestand
  • 29 Citaten (Scopus)
    320 Downloads (Pure)

    Decentralized dynamic understanding of hidden relations in complex networks

    Mocanu, D. C., Exarchakos, G. & Liotta, A., 1 dec 2018, In : Scientific Reports. 8, 1, 15 blz., 1571.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

    Open Access
    Bestand
  • 7 Citaten (Scopus)
    69 Downloads (Pure)

    Online contrastive divergence with generative replay: experience replay without storing data

    Mocanu, D. C., Torres Vega, M., Eaton, E., Stone, P. & Liotta, A., 18 okt 2016, In : arXiv. 16 blz., 1610.05555.

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademic

    Bestand
  • On the synergy of network science and artificial intelligence

    Mocanu, D. C., 2016, Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJCAI 2016). Palo Alto: AAAI Press

    Onderzoeksoutput: Hoofdstuk in Boek/Rapport/CongresprocedureConferentiebijdrageAcademicpeer review

    Open Access
    Bestand
  • Factored four way conditional restricted Boltzmann machines for activity recognition

    Mocanu, D. C., Bou Ammar, H., Lowet, D. J. C., Driessens, K., Liotta, A., Weiss, G. & Tuyls, K. P., 2015, In : Pattern Recognition Letters. 66, blz. 100-108

    Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

    Open Access
    Bestand
  • 24 Citaten (Scopus)
    107 Downloads (Pure)

    Prijzen

    Highly Commended Paper Award - International Journal of Pervasive Computing and Communications

    Decebal Mocanu (Ontvanger), 2017

    Prijs: AndersWerk, activiteit of publicatie gerelateerde prijzen (lifetime, best paper, poster etc.)Wetenschappelijk

    Travel Award at IJCAI 2016

    Decebal Mocanu (Ontvanger), 11 jul 2016

    Prijs: AndersBeurzenWetenschappelijk

    Master AI Thesis Award, 1st prize, Maastricht University, the Netherlands

    Decebal Mocanu (Ontvanger), 12 jul 2013

    Prijs: AndersWerk, activiteit of publicatie gerelateerde prijzen (lifetime, best paper, poster etc.)Wetenschappelijk

  • Best Paper Award MoMM2015

    Decebal Mocanu (Ontvanger), 13 dec 2015

    Prijs: AndersWerk, activiteit of publicatie gerelateerde prijzen (lifetime, best paper, poster etc.)Wetenschappelijk

    Certificate of appreciation from the Journal of Electronic Imaging for serving as a reviewer.

    Decebal Mocanu (Ontvanger), 1 jan 2015

    Prijs: AndersWerk, activiteit of publicatie gerelateerde prijzen (lifetime, best paper, poster etc.)Wetenschappelijk

    Activiteiten

    • 2 Bezoek externe academische instelling
    • 1 Aangemelde presentatie

    University of Texas at Austin

    Decebal Mocanu (Bezoekende onderzoeker)
    16 jan 201616 apr 2016

    Activiteit: Types bezoeken aan een externe instellingBezoek externe academische instellingWetenschappelijk

    "Deep Learning and its applicability" at University of Würzburg, Germany.

    Decebal Mocanu (Spreker)
    24 aug 201528 aug 2015

    Activiteit: Types gesprekken of presentatiesAangemelde presentatieWetenschappelijk

    University of Pennsylvania

    Decebal Mocanu (Bezoekende onderzoeker)
    15 sep 201415 dec 2014

    Activiteit: Types bezoeken aan een externe instellingBezoek externe academische instellingWetenschappelijk

    Cursussen

    CSE - Web Science

    1/09/15 → …

    Cursus

    Foundations of data mining

    1/09/1731/08/21

    Cursus

    Knipsels

    New AI method increases the power of artificial neural networks

    Decebal C. Mocanu

    20/06/18

    1 item van Media-aandacht

    Pers / media: Vakinhoudelijk commentaar

    -The University of Oslo: New AI method increases the power of artificial neural networks

    Decebal C. Mocanu

    20/06/18

    1 item van Media-aandacht

    Pers / media: Vakinhoudelijk commentaar

    Scriptie

    Block-sparse evolutionary training using weight momentum evolution: training methods for hardware efficient sparse neural networks

    Auteur: Hagebols, T., 29 apr 2019

    Begeleider: Mocanu, D. (Afstudeerdocent 1), Zhang, Y. (Afstudeerdocent 2) & Lowet, D. (Externe coach)

    Scriptie/masterproef: Master

    Evolving sparse neural networks using cosine similarity

    Auteur: Pieterse, J., 31 aug 2018

    Begeleider: Mocanu, D. (Afstudeerdocent 1)

    Scriptie/masterproef: Master

    Bestand

    Prediction and reduction of MRP nervousness by parameterization from a cost perspective

    Auteur: Linders, B., 28 feb 2019

    Begeleider: Dijkman, R. (Afstudeerdocent 1) & Mocanu, D. (Afstudeerdocent 2)

    Scriptie/masterproef: Master

    Bestand

    Unsupervised learning for early detection of merchant risk in payments

    Auteur: Bahulikar, S., 25 nov 2019

    Begeleider: Mocanu, D. C. (Afstudeerdocent 1) & Moura, J. (Externe persoon) (Externe coach)

    Scriptie/masterproef: Master

    Bestand