Curriculum Vitae - Dipl. Eng. Vasile V. Moca

First name:
Last name:
Date and place of birth:
Marital status:
Vasile Vlad
24.06.1979, Cluj-Napoca, Romania
Education and scientific activity:
  • 2007 - Present: Researcher in the Experimental and Theoretical Neuroscience Laboratory at the Center for Cognitive and Neural Studies (Coneural) in Cluj-Napoca, Romania.
  • 2005 - 2007: Invited researcher at Max Planck Institute for Brain Research and Frankfurt Institute for Advanced Studies.
  • 2004 - Present: PhD student at Technical University of Cluj-Napoca.
  • 2003 - 2004: Post university studies: Technical University of Cluj-Napoca, Faculty of Electronics and Telecommunications, Advanced techniques in Telecommunications.
  • 1998 - 2003: Technical University of Cluj-Napoca, Faculty of Electronics and Telecommunications, Applied Electronics. Graduated in 2003 with a degree mark of 9.75 out of 10.
  • 1994 - 1998: Computer Science High School "Tiberiu Popoviciu", Cluj-Napoca.
  • Romanian, native
  • English, fluent
  • French, average
  • Italian, average
Professional activity:
  • Employee of SC. Hanna Instruments Romania SRL from August 2003 to February 2005, working as software engineer in the R&D department on software design and implementation of embedded chemical measurement and control devices.
Description of scientific work:
  • The scientific work of ing. Vlad V. Moca takes two main directions. The first line of work is related to analysis and classification of biological signals from voice recognition to analysis of neuronal recordings. The main body of his work include: the classification of human EEG recording during anesthesia, study of dimensionality of local field potential recorded from the visual cortex of anesthetized cats and the modeling spike trains with realistic statistical properties. Future work will include the analysis of human EEG during visual perception and cognition tasks. The second direction is related to the analysis of neural networks. The second research direction focuses on artificial neural networks. In his previous work the artificial neural networks were used as simple classifiers, and recently its interest shifted towards the dynamics of activity in spiking artifficial neural networks. Lately the structural and topological reorganization of biological networks during learning are under focus as a source of inspiration for new models of learning in artificial spiking neural networks.
  • Moca VV, Scheller B, Muresan RC, Daunderer M, Pipa G (2009) EEG under anesthesia-feature extraction with TESPAR. Comput Methods Programs Biomed 95: 191-202.
  • Muresan RC, Jurjut OF, Moca VV, Singer W, Nikolic D (2008) The oscillation score: an efficient method for estimating oscillation strength in neuronal activity. J Neurophysiol 99: 1333-1353.
  • Nikolic D, Moca VV, Singer W, Muresan RC (2008) Properties of multivariate data investigated by fractal dimensionality. J Neurosci Methods 172: 27-33.
  • Moca VV, Nikolic D, Muresan RC (2008) Real and modeled spike trains: Where do they meet? In: Kurkov V, Neruda R, Koutnk J, editors, Proceedings of the 18th ICANN (2). Prague, Czech Republic: Springer, volume 5164 of Lecture Notes in Computer Science, pp. 488-497.
  • Moca VV, Scheller B, Pipa G, Lupu E (2007) TESPAR - towards biomedical applications. In: 1st International Conference on Advancements of Medicine and Health Care through Technology, MediTech2007. pp. 281-286
  • Moca VV (2006) TESPAR a biometric time domain approach to speaker recognition. Acta Technica Napocensis 47: 57-62.
  • Moca VV, Lupu E, Pop PG (2005) TESPAR coding method evaluation in speaker recognition experiments. In: Trends in Speech Technology Proceedings of the 3rd Conference Speech Technology and Human-Computer-Dialogue: SpeD 2005. Cluj-Napoca, Romania, pp. 201-212. ISBN 973-27-1178-7.
  • Moca VV (2005) TESPAR a robust voice biometric. In: Verificatori biometrici workshop Cluj-Napoca. Cluj-Napoca, Romania. ISBN 973-656-918-7.
  • Lupu E, Moca VV, Pop PG (2004) Application for TESPAR coding study and speaker recognition experiments. In: Scientific bulletin POLITEHNICA University of Timisoara, Proceedings of Symposium on Electronics and Telecomunicetions Etc 2004. Timisoara, Romania, volume 1, pp. 279-282. ISSN 1583-3380
  • Lupu E, Moca VV, Pop PG (2004) Environment for speaker recognition using speech coding. In: Proceedings of Communications. Bucharest, Romania, volume 1, pp. 199-204. ISBN 973-640-036-0.
  • Lupu E, Moca VV, Pop PG (2003) TESPAR coding study for speaker recognition. In: The 30th session of scientific presentations "Modern technologies in the XXI Century" Bucharest. Bucharest, Romania, pp. 214-221. ISBN 973-640-012-3.
Posters, abstracts and talks:
  • Moca VV, Scheller B, Muresan RC, Daunderer M, Pipa G (2009) EEG processing with TESPAR for depth of anesthesia detection. In: (CNS Meeting 09) Berlin Germany: BMC Neuroscience 10 (Suppl 1). Berlin, Germany, p. 68.
  • Muresan RC, Tincas I, Moca VV, Melloni L (2009) Probing the visual system with visual hypotheses. In: (CNS Meeting 09) Berlin Germany: BMC Neuroscience 10 (Suppl 1). Berlin, Germany, p. 356.
  • Moca VV, Scheller B, Muresan RC, Daunderer M, Pipa G (2009) Importance of EEG frequency bands in the assessment of depth of anesthesia. In: ASSC XIII. Berlin, Germany, p. 187.
  • Muresan RC, Tincas I, Moca VV, Melloni L (2009) Vision by inference: visual recognition under uncertainty. In: ASSC XIII. Berlin, Germany, p. 195.
  • Moca VV (2006) EEG under anesthesia - learning from human experience, Max Planck Society, Ringberg retreat, Germany.
  • Moca VV (2006) TESPAR and EEG under anesthesia FIGGS end of term seminar, Frankfurt Institute for Advanced Studies, Frankfurt, Germany.