Nousias Stavros
Research Associate Software engineer PhD Candidate

Resume

Education

  • 2016 MSc Electronics & Information Processing,
    • University of Patras Greece
  • 2011 Dipl.-ing Electrical & Computer Engineering,
    • University of Patras Greece

Experience

  • 2016-Present Research associate,
    • University of Patras Greece
  • 2015-2016 Research assistant,
    • University of Patras Greece
  • 2013-2014 DevOps Engineer,
  • 2012-2013 Full stack web developer,

Participation in Research Projects

  • GamECAR H2020 research and innovation programme (grant agreement n° 732068)
    • "Gamification of EcoDriving Behaviours through intelligent Management of Dynamic car and driver information",
    • Role 2017-2019 : Research Associate
  • MyAirCoach H2020 research programme (PHC 26-2014 RIA Project) MSc Electronics & Information Processing,
    • "Analysis, modelling and sensing of both physiological and environmental factors for the customized and predictive self-management of Asthma"
    • Role 2016-2018 : Research Associate

Skills

Publications

2018

  • A. S. Lalos, S. Nousias, and K. Moustakas,

    "GamECAR: Gamifying Self-Management of Eco-driving,"

    ERCIM News Spec. Theme Digit. Twins, 2018.
  • S. Nousias, A. S. Lalos, C. Tselios, D. Bintzas, D. Amaxilatis, I. Chatzigiannakis, G. Arvanitis, and K. Moustakas,

    “Gamification of EcoDriving Behaviours through Intelligent Management of dynamic car and driver information,”

    in European Project Space, SCITEPRESS, 2018.
  • S. Nousias, C. Tselios, D. Bitzas, A. S. Lalos, K. Moustakas, and I. Chatzigiannakis,

    "Uncertainty management for wearable IoT wristband sensors using Laplacian-based Matrix Completion,"

    in 2018 IEEE 23rd International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD), 2018.
  • G. Arvanitis, O. Kocsis, A. S. Lalos, S. Nousias, K. Moustakas, and N. Fakotakis,

    "3-Class Prediction of Asthma Control Status Using a Gaussian Mixture Model Approach,"

    in Proceedings of the 10th Hellenic Conference on Artificial Intelligence - SETN ’18, 2018, pp. 1–2.
  • S. Nousias, A. S. Lalos, G. Arvanitis, K. Moustakas, T. Tsirelis, D. Kikidis, K. Votis, and D. Tzovaras,

    "An mHealth System for Monitoring Medication Adherence in Obstructive Respiratory Diseases Using Content Based Audio Classification,"

    IEEE Access, vol. 6, pp. 11871–11882, 2018
  • S. Nousias, C. Tselios, D. Bintzas, O. Orfila, S. Jamson, P. Mejuto, D. Amaxilatis, O. Akrivopoulos, I. Chatzigiannakis, A. S. Lalos, and K. Moustakas,

    “Managing nonuniformities and uncertainties in vehicle-oriented sensor data over next generation networks,”

    in IEEE International Conference on Pervasive computing and communications, 2018.

2017

  • Lalas A, Nousias S, Kikidis D, Lalos A, Arvanitis G, Sougles C, Moustakas K, Votis K, Verbanck S, Usmani O, Tzovaras D.,

    "Substance deposition assessment in obstructed pulmonary system through numerical characterization of airflow and inhaled particles attributes."

    BMC Medical Informatics and Decision Making. 2017 Dec 1;17(3):173.

2016

  • A. Lalas, S. Nousias, D. Kikidis, A. Lalos, K. Moustakas, K. Votis, O. Usmani, and D. Tzovaras,

    "Numerical Assessment of Airflow and Inhaled Particles Attributes in Obstructed Pulmonary System,"

    in IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2016.
  • S. Nousias, A. S. Lalos, and K. Moustakas,

    "Computational Modeling for Simulating Obstructive Lung Diseases Based on Geometry Processing Methods,"

    in Digital Human Modeling: Applications in Health, Safety, Ergonomics and Risk Management, 2016, pp. 100–109.
  • S. Nousias, A. Lalos, K. Moustakas, A. Lalas, D. Kikidis, K. Votis, D. Tzovaras, O. Usmani, and K. F. Chung,

    "Computational modeling methods for simulating obstructive human lung diseases,"

    in European Respiratory Society International Congress, 2016.
  • S. Nousias, J. Lakoumentas, A. Lalos, D. Kikidis, K. Moustakas, K. Votis, and D. Tzovaras,

    "Monitoring asthma medication adherence through content based audio classification,"

    in IEEE Symposium Series on Computational Intelligence, 2016.