
Dottorando in Ingegneria Informatica E Dei Sistemi , 36o cycle (2020-2023)
Dipartimento di Automatica e Informatica (DAUIN)
Docente esterno e/o collaboratore didattico
Dipartimento di Automatica e Informatica (DAUIN)
Profilo
Dottorato di ricerca
Argomento di ricerca
Data Analytics and Big Spatio-Temporal Data
Tutori
Interessi di ricerca
Biografia
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, Apache Spark and Apache Storm frameworks. Data analysis and data mining algorithms are considered both in an offline and online context: spatio-temporal data can be exploited in real-time systems to analyze data streams in many different fields such as natural hazards, disaster prevention, environmental monitoring systems and smart cities.
His main research topics are: Big Data Analytics, Data Mining and Machine Learning.
Premi e riconoscimenti
- PhD Quality Awards 2023 document (2023)
- 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)
Didattica
Insegnamenti
Corso di laurea magistrale
- 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
- 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
Pubblicazioni
Pubblicazioni più recenti Vedi tutte le pubblicazioni su Porto@Iris
- 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) - 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. ISSN 2168-6831
Contributo su Rivista - Colomba, Luca; Cagliero, Luca; Garza, Paolo (2023)
Density-based Clustering by Means of Bridge Point Identification. In: IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, pp. 1-14. ISSN 1041-4347
Contributo su Rivista - 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 (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)