Monica Visintin

Confirmed Associate Professor
Department of Electronics and Telecommunications (DET)

Profile

Research interests

Self organizing networks

Scientific branch

ING-INF/03 - TELECOMMUNICATIONS
(Area 0009 - Industrial and information engineering)

Research topics

  • Self Organizing Networks (SON): KPI prediction, anomaly detection using machine learning techniques

Skills

ERC sectors

PE7_6 - Communication technology, high-frequency technology
PE6_11 - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
PE7_7 - Signal processing
PE7_3 - Simulation engineering and modelling

SDG

Goal 3: Good health and well-being
Goal 9: Industry, Innovation, and Infrastructure

Teaching

Collegi of the degree programmes

Teachings

Master of Science

MostraNascondi A.A. passati

Bachelor of Science

  • Analisi dei segnali. A.A. 2023/24, INGEGNERIA BIOMEDICA. Collaboratore del corso
  • Teoria ed elaborazione dei segnali. A.A. 2022/23, INGEGNERIA DEL CINEMA E DEI MEZZI DI COMUNICAZIONE. Collaboratore del corso
  • Analisi dei segnali. A.A. 2022/23, INGEGNERIA BIOMEDICA. Collaboratore del corso
  • Signals and systems. A.A. 2021/22, ELECTRONIC AND COMMUNICATIONS ENGINEERING (INGEGNERIA ELETTRONICA E DELLE COMUNICAZIONI). Collaboratore del corso
  • Signals and systems. A.A. 2020/21, ELECTRONIC AND COMMUNICATIONS ENGINEERING (INGEGNERIA ELETTRONICA E DELLE COMUNICAZIONI). Collaboratore del corso
  • Signals and systems. A.A. 2019/20, ELECTRONIC AND COMMUNICATIONS ENGINEERING (INGEGNERIA ELETTRONICA E DELLE COMUNICAZIONI). Collaboratore del corso
  • Signals and systems. A.A. 2018/19, ELECTRONIC AND COMMUNICATIONS ENGINEERING (INGEGNERIA ELETTRONICA E DELLE COMUNICAZIONI). Collaboratore del corso
  • Workshop " Circuits and algorithms for music processing". A.A. 2018/19, ELECTRONIC AND COMMUNICATIONS ENGINEERING (INGEGNERIA ELETTRONICA E DELLE COMUNICAZIONI). Collaboratore del corso
MostraNascondi A.A. passati

Research

Research fields

Research projects

Projects funded by commercial contracts

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Supervised PhD students

  • Riccardo Schiavone. Programme in Ingegneria Elettrica, Elettronica E Delle Comunicazioni (37th cycle, 2021-in progress)
    Research subject: Researching efficient and low-complexity waveforms for machine type communications (mMTC and URLLC)
    Big Data, Machine Learning, Neural Networks and Data Science
    Communication and Computer Networks
    Optical and Wireless Digital Transmissions Systems
    Big Data, Machine Learning, Neural Networks and Data Science
    Communication and Computer Networks
    Optical and Wireless Digital Transmissions Systems
    Big Data, Machine Learning, Neural Networks and Data Science
    Communication and Computer Networks
    Optical and Wireless Digital Transmissions Systems

Publications

PoliTO co-authors

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