Alessandro Paolo Daga

Fixed-term tenure-track assistant professor
Department of Mechanical and Aerospace Engineering (DIMEAS)


Research interests

Bearings (machine parts)
Digital signal processing
Machine condition monitoring
Machine diagnostics
Machine learning
Statistical learning
Vibration monitoring


Tracking the “signature” of a machine (the characteristic features of the machine extracted from the vibration signal, usually from accelerometers) evolving over time, it is possible to identify the main causes of vibration and preventively recognize damage and wear of the components, thus performing an accurate diagnosis. Two steps are fundamental: • Signal processing is exploited to highlight and extract damage-characteristic features. • Machine learning is employed to automatically infer anomalies in the vibration response from the extracted features. Such anomaly or novelty, in fact, can be put in relation to damage when confounding influences (i.e. different operational or environmental conditions) can be excluded or compensated. The aim is to create a reliable diagnostic system to be integrated into machine maintenance regimes so as to foster safety while, at the same time, saving on costs


ERC sectors

PE1_19 - Control theory and optimisation
PE6_11 - Machine learning, statistical data processing and applications using signal processing (e.g. speech, image, video)
PE8_7 - Mechanical and manufacturing engineering (shaping, mounting, joining, separation)
PE1_10 - ODE and dynamical systems
PE1_18 - Scientific computing and data processing
PE7_7 - Signal processing
PE1_14 - Statistics


Goal 7: Affordable and clean energy
Goal 9: Industry, Innovation, and Infrastructure

Open badges

Awards and Honors

  • Contest della conferenza internazionale “Surveillance 8” - 2° classificato conferred by Organization committee of the contest presented at the 8th International Conference Surveillance 8 (2015)
  • Contest della conferenza internazionale “Surveillance 9” - 1° classificato conferred by Organization committee of the contest presented at the 9th International Conference Surveillance 9 (2017)
  • Contest della conferenza internazionale “Survishno” - 2° classificato conferred by Organization committee of the contest presented at the International Conference Survishno (2019)
  • Miglior Paper presentato alla conferenza virtuale IEEE MetroInd4.0&IoT 2020 - 3° classificato conferred by Organization committee of the IEEE MetroInd4.0&IoT 2020 virtual conference (2020)

Editorial boards

  • APPLIED SCIENCES (2020-2022), Guest Editor of magazine or editorial series


Collegi of the degree programmes



MostraNascondi A.A. passati

Master of Science

MostraNascondi A.A. passati

Bachelor of Science

MostraNascondi A.A. passati


Research groups

Research projects

Projects funded by competitive calls


PoliTO co-authors

Last years publications

Publications by type

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