Data science for geo-referenced and heterogeneous data

• Distinctive Mention to the authors of paper "Deep Learning models for passability detection of flooded roads", presented the 31/10/2018 at MediaEval 2018 Workshop (2018)
• Best Student Paper Nominee to the authors of the paper "Supervised Burned Areas delineation by means of Sentinel-2 imagery and Convolutional Neural Networks" accepted and published to the ISCRAM2020 conference. (2020)

Master of Science

• Big data: architectures and data analytics. A.A. 2017/18, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
• Big data: architectures and data analytics. A.A. 2018/19, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
• Big data: architectures and data analytics. A.A. 2019/20, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso

• Monaco, Simone; Greco, Salvatore; Farasin, Alessandro; Colomba, Luca; Apiletti, Daniele; ... (2021)
  Attention to Fires: Multi-Channel Deep Learning Models for Wildfire Severity Prediction. In: APPLIED SCIENCES, vol. 11. ISSN 2076-3417
  Contributo su Rivista
• Monaco, Simone; Pasini, Andrea; Apiletti, Daniele; Colomba, Luca; Farasin, Alessandro; ... (2021)
  Double-Step deep learning framework to improve wildfire severity classification. In: Workshops of the 24th International Conference on Extending Database Technology/24th International Conference on Database Theory, EDBT-ICDT 2021, Nicosia (Cyprus), March 23-26, 2021. ISBN: 978-3-89318-084-4
  Contributo in Atti di Convegno (Proceeding)
• Farasin, Alessandro (2021)
  Data science for geo-referenced and heterogeneous data analysis with applications in the emergency management domain. relatore: GARZA, PAOLO; , 33. XXXIII Ciclo, P.: 157
  Doctoral Thesis
• Palomba, Giulio; Farasin, Alessandro; Rossi, Claudio (2020)
  Sentinel-1 Flood Delineation with Supervised Machine Learning. In: 17th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2020), Blacksburg, Virginia (USA), May 24-27, 2020, pp. 1072-1083
  Contributo in Atti di Convegno (Proceeding)
• Farasin, Alessandro; Colomba, Luca; Garza, Paolo (2020)
  Double-Step U-Net: A Deep Learning-Based Approach for the Estimation of Wildfire Damage Severity through Sentinel-2 Satellite Data. In: APPLIED SCIENCES, vol. 10. ISSN 2076-3417
  Contributo su Rivista
• Arnaudo, Edoardo; Farasin, Alessandro; Rossi, Claudio (2020)
  A Comparative Analysis for Air Quality Estimation from Traffic and Meteorological Data. In: APPLIED SCIENCES, vol. 10. ISSN 2076-3417
  Contributo su Rivista
• Lopez Fuentes, Laura; Farasin, Alessandro; Zaffaroni, Mirko; Skinnemoen, Harald; Garza, ... (2020)
  Deep learning models for road passability detection during flood events using social media data. In: APPLIED SCIENCES, vol. 10. ISSN 2076-3417
  Contributo su Rivista
• Farasin, Alessandro; Colomba, Luca; Palomba, Giulio; Nini, Giovanni; Rossi, Claudio (2020)
  Supervised Burned Areas delineation by means of Sentinel-2 imagery and Convolutional Neural Networks. In: 17th International Conference on Information Systems for Crisis Response And Management (ISCRAM 2020), Blacksburg, Virginia (USA), May 24-27, 2020, pp. 1060-1071
  Contributo in Atti di Convegno (Proceeding)
• Rossi, C.; Farasin, A.; Falcone, G.; Castelluccio, C. (2019)
  A Machine Learning Approach to Monitor Air Quality from Traffic and Weather data. In: 2019 Joint Poster and Workshop Sessions of AmI, AmI 2019 and 2019 European Conference on Ambient Intelligence, (IT), 2019, pp. 66-74. ISSN 1613-0073
  Contributo in Atti di Convegno (Proceeding)
• Linty, Nicola; Farasin, Alessandro; Favenza, Alfredo; Dovis, Fabio (2019)
  Detection of GNSS Ionospheric Scintillations based on Machine Learning Decision Tree. In: IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS, vol. 55, pp. 303-317. ISSN 0018-9251
  Contributo su Rivista
• Farasin, Alessandro; Nini, Giovanni; Garza, Paolo; Rossi, Claudio (2019)
  Unsupervised Burned Area Estimation through Satellite Tiles: A multimodal approach by means of image segmentation over remote sensing imagery. In: MACLEAN: MAChine Learning for EArth ObservatioN (workshop @ECML/PKDD2019), Wurzburg (DE), 20/09/2019, pp. 1-10
  Contributo in Atti di Convegno (Proceeding)
• Zaffaroni, Mirko; Lopez Fuentes, Laura; Farasin, Alessandro; Garza, Paolo; Skinnemoen, ... (2019)
  AI-Based Flood Event Understanding and Quantifying Using Online Media and Satellite Data. In: MediaEval 2019 Multimedia Benchmark Workshop, EURECOM - Sophia Antipolis, 27/10/2019, pp. 1-3. ISSN 1613-0073
  Contributo in Atti di Convegno (Proceeding)
• Rossi, C.; Farasin, A.; Falcone, G.; Castelluccio, C. (2019)
  uAQE: Urban Air Quality Evaluator. In: AMI2019: European Conference on Ambient Intelligence 2019, Roma, 13/11/2019 - 15/11/2019, pp. 337-343. ISBN: 978-3-030-34255-5
  Contributo in Atti di Convegno (Proceeding)
• Lopez-Fuentes, Laura; Farasin, Alessandro; Skinnemoen, Harald; Garza, Paolo (2018)
  Deep Learning Models for Passability Detection of Flooded Roads. In: Working Notes Proceedings of the MediaEval 2018 Workshop, Sophia Antipolis, France, 29-31 October 2018, Sophia Antipolis, France., 29/10/2018 - 31/10/2018. ISSN 1613-0073
  Contributo in Atti di Convegno (Proceeding)
• Farasin, Alessandro; Garza, Paolo (2018)
  PERCEIVE: Precipitation Data Characterization by means on Frequent Spatio-Temporal Sequences. In: 15th International Conference on Information Systems for Crisis Response and Management (ISCRAM 2018), In-Cooperation with ACM SIGCAS, Rochester, NY (USA), May 20-23, 2018, pp. 1081-1088. ISBN: 978-0-692-12760-5
  Contributo in Atti di Convegno (Proceeding)