TO - Artur Miroszewski
Researcher (Adiunkt) w Uniwersytet Jagielloński, Uniwersytet Jagielloński, 2024
Activities: Quantum machine learning Linkedin
Teaching
TO - Amer Delilbasic
PhD Student in Computational Engineering, Forschungszentrum Jülich, 2024
Activities: Quantum machine learning Linkedin
QOSF Mentor - Samuel Vidal Gallego
Quantum Machine Learning Researcher, IKERLAN, 2024
Activities: Quantum machine learning Linkedin
QOSF Mentor - Sebastian Mair
Software Engineer, Quantum Industries GmbH, 2024
Activities: Quantum machine learning Linkedin
Supporting Ph.D.- Luigi Russo
Ph.D. in Information technology for engineering, University of Sannio and University of Pavia, 2024
Ph.D. Activities: Climate Change Impact Evaluation on levels of water resources through deep learning techniques
Supporting Ph.D.- Francesco Mauro
Ph.D. in Information technology for engineering, University of Sannio, Engineering Department, 2024
Ph.D. Activities: Climate Change Impact Evaluation on levels of water resources through deep learning techniques and Quantum Computing for Earth Observation
Supporting Ph.D. - Francesca De Falco
Ph.D. in Information and Communication Engineering, La Sapienza University of Rome, 2024
Ph.D. Activities: Quantum machine learning
Supporting Ph.D. - Andrea Ceschini
Ph.D. in Information and Communication Engineering, La Sapienza University of Rome, 2024
Ph.D. Activities: Quantum Machine Learning on NISQ devices
Supporting Ph.D. - Andrea Carbone
National Ph.D. in Earth Observation, La Sapienza University of Rome, 2024
Ph.D. Activities: Quantum machine learning
Master Thesis Co-Supervisor - Francesca De Falco
Master Degree in Electronic Engineering, La Sapienza University of Rome, Engineering Department, 2023
Thesis title: Quantum Hybrid Diffusion Models
Master Thesis Co-Relator - Francesco Mauro
Master Degree in Electronic Engineering for Automation and Telecommunications, University of Sannio, Engineering Department, 2022
Thesis title: Climate Change Impact Evaluation on levels of water resources through deep learning techniques
Bachelor Thesis Co-Relator - Pietro Di Stasio
Bachelor Degree in Electronic Engineering for Automation and Telecommunications, University of Sannio, Engineering Department, 2022
Thesis title: Use of Sentinel-5P data for the early detection of volcanic eruptions through on-board Artificial Intelligence
Bachelor Thesis Co-Relator - Giovanni Pagnozzi
Bachelor Degree in Electronic Engineering for Automation and Telecommunications, University of Sannio, Engineering Department, 2022
Thesis title: Analysis of large strategic structures using the PyGMTSAR tool on Sentinel-1 data
Bachelor Thesis Co-Relator - Simona Reale
Bachelor Degree in Electronic Engineering for Automation and Telecommunications, University of Sannio, Engineering Department, 2021
Thesis title: Performance analysis of a new splitting method for datasets in machine learning models. Case study: detection of volcanic eruptions
Bachelor Thesis Co-Relator - Luigi Russo
Bachelor Degree in Electronic Engineering for Automation and Telecommunications, University of Sannio, Engineering Department, 2021
Thesis title: Development of a Machine Learning model based on the “categorical boosting” technique for the correlation between tropospheric NO2 and NO2 on the ground
Bachelor Thesis Co-Relator - Tony De Corso
Bachelor Degree in Electronic Engineering for Automation and Telecommunications, University of Sannio, Engineering Department, 2020
Thesis title: Application of DInSAR technique to high coherence satellite images for strategic infrastructure monitoring: Morandi Bridge
Bachelor Thesis Co-Relator - Morena Gismondi
Bachelor Degree in Electronic Engineering for Automation and Telecommunications, University of Sannio, Engineering Department, 2020
Thesis title: Use of Sentinel-5P data for the analysis of the correlation between NO2 levels and mobility data in areas with a high number of infections due to Covid-19. Case study: Lombardy Region.
Bachelor Thesis Advisor - Luca Mignone
Bachelor Degree in Electronic Engineering for Automation and Telecommunications, University of Sannio, Engineering Department, 2020
Thesis title: Use of differential interferometry on Sentinel-1 images for the measurement of earthquake-induced ground displacements.
Bachelor Thesis Advisor - Gianluca Di Cosmo
Bachelor Degree in Electronic Engineering for Automation and Telecommunications, University of Sannio, Engineering Department, 2020
Thesis title: Use of Sentinel-5P data for the analysis of the correlation between NO2 levels and the number of infections due to Covid-19. Case study: Wuhan area
Bachelor Thesis Co-Relator - Francesco Mauro
Bachelor Degree in Electronic Engineering for Automation and Telecommunications, University of Sannio, Engineering Department, 2020
Thesis title: Analysis of the correlation between Sentinel-5P data and epidemiological data. Case study: spread of Covid-19 in the Lombardy region