Ph.D. in Ingegneria Informatica E Dei Sistemi , 36th cycle (2020-2023)
Ph.D. obtained in 2024
Dissertation:
Spatial data science: from aerial data to discrete spatio-temporal event analysis (Abstract)
Tutors:
Paolo GarzaProfile
Research topic
Data Analytics and Big Spatio-Temporal Data
Research interests
Biography
He is interested in the application of data mining and machine learning algorithms to large volumes of data, with a focus on geospatial and temporal information, in order to extract valuable information, perform predictions and identify patterns using Python's data science ecosystem, including Apache Spark framework. Moreover, he published several research papers in the field of remote sensing, Earth Observation and deep learning, focusing on emergency managament and land cover classification.
His main research topics are: Big Data Analytics, Data Mining and Machine Learning.
Awards and Honors
- PhD Quality Awards 2023 document (2023)
- Volunteer at ECML/PKDD2023 conference (Torino, 18-22 September 2023) (2023)
- 2nd year PhD Quality Award (2nd prize) (2024)
- Travel Grant Award to PhD Students for SIGSPATIAL2022 conference, given to volunteers who helped throughout the conference. (2023)
- 2nd place at Waste Classification Challenge held during International Summer School on Deep Learning 2021 (ISSonDL2021): the challenge consisted in developing and training a Deep Learning model to perform binary classification on images. Images represented different items that needed to be classified either as "Recyclable" or "Organic". To make the challenge more difficult, the organisers randomly added noise to all images in the form of random black rectangles. (2021)
Teaching
Teachings
Master of Science
- Big data processing and analytics. A.A. 2022/23, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Big data processing and analytics. A.A. 2023/24, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Challenge@PoliTo by Students PoliTO - Living with natural risks. A.A. 2023/24, INGEGNERIA GESTIONALE (ENGINEERING AND MANAGEMENT). Collaboratore del corso
- Big data: architectures and data analytics. A.A. 2020/21, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Big data: architectures and data analytics. A.A. 2021/22, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Big data: architectures and data analytics. A.A. 2022/23, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Big data: architectures and data analytics. A.A. 2023/24, INGEGNERIA INFORMATICA (COMPUTER ENGINEERING). Collaboratore del corso
- Distributed architectures for big data processing and analytics. A.A. 2020/21, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
- Distributed architectures for big data processing and analytics. A.A. 2021/22, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
- Distributed architectures for big data processing and analytics. A.A. 2022/23, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
- Applied data science project. A.A. 2021/22, DATA SCIENCE AND ENGINEERING. Collaboratore del corso
Research
Research groups
Publications
Works published during the Ph.D. View all publications in Porto@Iris
- Colomba, Luca (2024)
Spatial data science: from aerial data to discrete spatio-temporal event analysis. relatore: GARZA, PAOLO; , 36. XXXVI Ciclo, P.: 132
Doctoral Thesis - Colomba, Luca; Garza, Paolo (2023)
ViGEO: an Assessment of Vision GNNs in Earth Observation. In: International Workshop on Spatial and Spatiotemporal Data Mining (SSTDM workshop at ICDM2023), Shanghai, China, 01/12/2023 - 04/12/2023, pp. 816-822
Contributo in Atti di Convegno (Proceeding) - Rege Cambrin, Daniele; Colomba, Luca; Garza, Paolo (2023)
Vision Transformers for Burned Area Delineation. In: MACLEAN: MAChine Learning for EArth ObservatioN (workshop @ECML/PKDD2022), Grenoble (FR), 19/09/2022
Contributo in Atti di Convegno (Proceeding) - Colomba, Luca; Cagliero, Luca; Garza, Paolo (2023)
Density-based Clustering by Means of Bridge Point Identification. In: IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, vol. 35, pp. 11274-11287. ISSN 1041-4347
Contributo su Rivista - Rege Cambrin, Daniele; Colomba, Luca; Garza, Paolo (2023)
CaBuAr: California burned areas dataset for delineation [Software and Data Sets]. In: IEEE GEOSCIENCE AND REMOTE SENSING MAGAZINE, vol. 11, pp. 106-113. ISSN 2168-6831
Contributo su Rivista - Koudounas, Alkis; LA QUATRA, Moreno; Vaiani, Lorenzo; Colomba, Luca; Attanasio, ... (2023)
ITALIC: An Italian Intent Classification Dataset. In: INTERSPEECH 2023, Dublin (Ireland), 20 August - 24 August 2023, pp. 2153-2157
Contributo in Atti di Convegno (Proceeding) - Colomba, Luca; Farasin, Alessandro; Monaco, Simone; Greco, Salvatore; Garza, Paolo; ... (2022)
A Dataset for Burned Area Delineation and Severity Estimation from Satellite Imagery. In: International Conference on Information and Knowledge Management (CIKM) 2022, Atlanta (Georgia, USA), 17/10/2022 - 21/10/2022, pp. 3893-3897. ISBN: 978-1-4503-9236-5
Contributo in Atti di Convegno (Proceeding) - Colomba, Luca; Cagliero, Luca; Garza, Paolo (2022)
Mining SpatioTemporally Invariant Patterns. In: International Conference on Advances in Geographic Information Systems (SIGSPATIAL) 2022, Seattle, Washington (USA), 01/11/2022 - 04/11/2022. ISBN: 978-1-4503-9529-8
Contributo in Atti di Convegno (Proceeding) - Cipriano, Marco; Colomba, Luca; Garza, Paolo (2021)
A Data-Driven Based Dynamic Rebalancing Methodology for Bike Sharing Systems. 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) - 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; Garza, Paolo; Baralis, ... (2020)
Improving Wildfire Severity Classification of Deep Learning U-Nets from Satellite Images. In: 2020 IEEE International Conference on Big Data, Atlanta (US), December 10-13, 2020, pp. 5786-5788. ISBN: 978-1-7281-6251-5
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 - 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)