Silvia Liberata Ullo

Information

Bio

I am Silvia Liberata Ullo, a professor and researcher in the field of Quantum Machine Learning applied to Remote Sensing with a solid foundation in Statistics and Signal Processing. My professional journey began at the University Federico II of Naples (Italy) in 1989, and then at the Massachusetts Institute of Technology (MIT) of Cambridge (U.S.A.), where I could earn my expertise both in engineering and management. With my skills, I have contributed first to ITALTEL S.p.A., a telecommunications company, for about 10 years, and to a public Municipality for 4 years. In 2004, I joined the Engineering Department of the University of Sannio.

Current Role

Since 2004, I have been teaching several courses in the field of Telecommunications and Electronics (bachelor, master, and PhD programs). Recent courses: Signal theory and elaboration, Probability and Signals, Telecommunication networks (Bachelor program); Earth monitoring and mission analysis Lab (Master program), Optical and radar remote sensing (Ph.D. program). I have been collaborating with public and private universities and institutions at a national and international level and supervising many PhD students. I am a Member of the Academic Senate and PhD Professors’ Board. I am an IEEE Senior Member, President of IEEE Aerospace and Electronic Systems (AES) Italy Chapter, and Europe Liaison for IEEE Geoscience and Remote Sensing Society (GRSS). Member of the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE GRSS. Co-Editor in Chief for the IET Image Processing journal. Associate Editor of relevant journals (IEEE TGRS, JSTARS, GRSL and others). Guest Editor of many special issues. I authored 90+ research papers, co-authored many book chapters and served as editor of two books.

Areas of Expertise

My expertise lies in several key areas of telecommunication engineering, including probability, statistics, and signal processing. My scientific skills allowed me to work on specific projects and topics related to radar systems, sensor networks, smart grids, remote sensing, satellite data analysis, machine learning (ML), and quantum ML. All the above can significantly benefit ESA Φ-lab CIN by supporting ESA Φ-lab CIN's goals or projects dealing with climate change, risk analysis, edge computing, AI on board, and many others.

Vision for the Future

I am dedicated to making my research a benefit for Humanity and my time a benefit for young researchers and students, supporting them in reaching their goals. 

Project as CIN Researcher

⚠️ Project is ongoing