Information
📚 Organization | ESA Φ-lab, Research Fellow |
📆 Period @ ESA Φ-lab | 2022 - 2025 |
🌍 Project @ ESA CIN | |
📍 GitHub | |
🌐 Website / Portfolio | |
🔨 Linkedin | |
📝 Publications |
Bio
Alessandro Sebastianelli received the degree (cum laude) in electronic engineering for automation and telecommunications from the University of Sannio where he also pursed the Ph.D. degree in Information Technologies for Engineering. His field of expertise covers remote sensing and satellite data analysis, artificial intelligence for earth observation and quantum computing. He coauthored a book and several articles to reputed journals and conferences for the sector of remote sensing. He received an IEEE award for one the best three theses in geoscience and remote sensing. He has been firstly a visiting researcher and later a research fellow at ESA Φ-lab. He has won an ESA OSIP proposal in August 2020. He is leading the working group on quantum computing for EO in the QUEST IEEE GRSSS technical committee. In his spare time he enjoys photography instagram page/photographer portfolio.
Current Role
Currently, I serve as a Research Fellow in Quantum Computing for Earth Observation at the European Space Agency, Φ-lab in Frascati (Italy), where I act as the technical officer for the QC4EO OSIP contracts and manage activities under the Invitation to Tender (ITT) on Quantum Computing for Earth Observation (QC4EO) and Blockchain for Earth Observation (Blockchain4EO). Additionally, I am dedicated to advancing research in quantum computing, quantum machine learning, and quantum technologies for their application in Earth Observation (EO) and the broader space sector, with a strong focus on enhancing the operational readiness and practical deployment of these emerging technologies. I also serve as a Technology Evaluation Board (TEB) expert evaluator, contributing to the assessment and strategic direction of innovative EO research initiatives.
Areas of Expertise
My expertise lies in several key areas of Earth Observation and Quantum Technologies, including remote sensing, machine learning and deep learning for EO, and quantum computing and quantum machine learning applied to EO. These specialisations enable me to develop and evaluate advanced, operationally relevant solutions that harness the potential of AI and quantum technologies to address complex challenges in EO data analysis and satellite-based information extraction. This multidisciplinary skill set can significantly benefit ESA Φ-lab by driving innovation in next-generation EO capabilities, supporting the maturation of quantum-enabled methods, and aligning with Φ-lab's mission to push the frontier of space data exploitation through cutting-edge research and technology integration.
Vision for the Future
Driven by a vision of a future where quantum technologies, advanced AI, and Earth Observation synergistically enable real-time, accurate, and sustainable monitoring of our planet, I am committed to pioneering research that bridges quantum computing and machine learning with operational EO applications. My long-term goal is to accelerate the transition of cutting-edge technologies from laboratory concepts to practical tools that support climate resilience, environmental monitoring, and space-based decision-making. By pushing the frontiers of EO through innovation in quantum and AI-driven methods, I aim to contribute to a future where space assets provide even deeper insights for science, policy, and society. This vision is fully aligned with ESA Φ-lab’s mission to incubate disruptive ideas for the space sector.