Paola Mazzoglio

PhD Student

Politecnico di Torino

Dipartimento di Ingegneria dell’Ambiente,

del Territorio e delle Infrastrutture Duca degli Abruzzi, 24

10129, Torino, Italy

Tel.: +39-011-090-5674



Born in Alessandria (AL), 24th February 1991.

  • Since November 2019: Ph.D. Student in Civil and Environmental Engineering at Politecnico di Torino. Supervisors: Prof. Pierluigi Claps, Prof. Ilaria Butera.
  • June 2017 – October 2019: GIS, remote sensing and hydrological modelling specialist at ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action), Torino.
  • February 2017: Successfully passed the qualification exam for the profession of engineer (section A, civil/environmental sector).
  • October 2016 – June 2017: Research grant at DIATI Department of Politecnico di Torino. Advisor: Prof. Francesco Laio. Research topic: “Analysis of the interaction between artificial light sources and rain fields for the development of an estimation precipitation method from photographic images”.
  • September 2016 – June 2018: Data scientist at WaterView SRL, Torino.
  • July 2016: Master’s Degree in Civil Engineering (Hydraulic specialization) at Politecnico di Torino. Title of the dissertation: “Laboratory experiment supporting an estimating precipitation method from photographic images”. Supervisors: Prof. Francesco Laio, Eng. Paolo Cavagnero.
  • March 2014: Bachelor’s Degree in Civil Engineering at Politecnico di Torino.


  • Spatial analysis of extreme rainfall.
  • Early warning systems.
  • Remote sensing.



  • Parodi A., Danovaro E., Hawkes J., Quintino T., Lagasio M., Delogu F., D’Andrea M., Parodi A., Sardo B.G., Ajmar A., Mazzoglio P., Brocheton F., Ganne L., García-Hernández R.J., Hachinger S., Hayek M., Terzo O., Krenek J., Martinovic J., 2021. LEXIS Weather and Climate Large-Scale Pilot. In: Barolli L., Poniszewska-Maranda A., Enokido T. (eds). Complex, Intelligent and Software Intensive Systems. CISIS 2020. Advances in Intelligent Systems and Computing, vol 1194. Springer, Cham.
  • Mazzoglio P., Balbo S., Laio F., Boccardo P., Pasquali P., 2020. ERDS: un sistema open source per il monitoraggio di eventi di pioggia intensa. FOSS4G Italia 2020.
  • Mazzoglio P., Laio F., Balbo S., Boccardo P., 2019. ERDS: an Extreme Rainfall Detection System based on both near real-time and forecast rainfall measurements. Eighth Bulgarian-Austrian Seminar “Hydrological hazards and related problems”, 30/31 May 2019, Sofia (Bulgaria).
  • Mazzoglio P., Laio F., Sandu C., Boccardo P., 2019. Assessment of an Extreme Rainfall Detection System for flood prediction over Queensland (Australia). 3rd International Electronic Conference on Remote Sensing (ECRS-3). Proceedings, 2019, 18(1), 1.
  • Mazzoglio P., Boccardo P., Laio F., Balbo S., Disabato F., 2018. ERDS: a satellite-based approach in the extreme rainfall detection field. AIT 2018 – IX Conference of the Italian Society of Remote Sensing, Firenze (Italy). (page 137).
  • Mazzoglio P., Laio F., Disabato F., Angeluccetti I., 2018. GPM precipitation data as input for a real time extreme rainfall detection system. 2018, EGU General Assembly, Vienna (Austria).
  • Angeluccetti I., Disabato F., Perez F., Balbo S., Mazzoglio P., Keramitsoglou I., Kiranoudis C.T., 2018. TRIBUTE ‘TRIgger Buffers for inundaTion Events’: the importance of flood hazard and vulnerability assessment. 2018, EGU General Assembly, Vienna (Austria).


  • Seminari Internacional sobre planificació i gestió del risc d’inundació en ambients mediterranis. 6 March 2019, Palma de Mallorca (Spain). “An extreme rainfall detection system based on near real-time measurements”. Authors: Paola Mazzoglio, Irene Angeluccetti. Presented as Oral.
  • Flood forecasting meets machine learning Workshop. 16/17 January 2019, Google campus in Tel Aviv. “Extreme rainfall detection system based on both near real-time and forecast rainfall measurements”. Author: Paola Mazzoglio. Presentation:
  • TRIBUTE Workshop. 26 September 2018, Torino (Italy). “The ITHACA contribution to the TRIBUTE project”. Author: Paola Mazzoglio. Presented as Oral.
  • TRIBUTE Workshop. 14 June 2018, Palma de Mallorca (Spain). “TRIBUTE in the flood events in Piedmont area”. Authors: Paola Mazzoglio, Stefano Pensa. Presented as Oral.


  • Open Days dell’Innovazione. 6/7 March 2019, Torino (Italy). Invited speaker at the “Agri – Tech” discussion table.


  • February 2019 – November 2019: Collaboration in the “Weather and Climate” Pilot of LEXIS (Large-scale EXecution for Industry & Society) H2020 project.
  • November 2018 – December 2018: Collaboration in the project “Global Land High Resolution Hot Spot Monitoring” within the “Global Land Component” of the Copernicus Land Service (C-GL-HRM) – Lot 1 ( Land cover and land cover change analysis and validation.
  • September 2018 – October 2018: Collaboration for a long-term consultancy to the European Environment Agency in implementing the In-Situ component of the Copernicus programme (, with a particular focus on the mapping component of the Copernicus Emergency Management Service.
  • August 2018 – September 2018: Analysis of available rainfall measurement for the upgrade of a drought monitoring early warning system (
  • April 2018 – October 2019: Management and elaboration of geospatial information in the framework of “Copernicus Emergency Management Service” ( On-demand and fast provision (within hours or days) of geospatial information derived from satellite remote sensing and completed by available in situ or open data sources in support of the emergency management activities immediately following an emergency event.
  • June 2017 – ongoing: Development and validation of an extreme rainfall detection system based on both near real-time and forecast rainfall measurement (ERDS – Extreme Rainfall Detection System –
  • June 2017 – December 2018: Participation in the project TRIBUTE (TRigger BUffer zones for inundaTion Events), Prevention Project for EU Civil Protection, DG-ECHO 2017-2018. Improvement of a satellite-based extreme rainfall detection system, analysis and elaboration of precipitation data.