Creating and sharing knowledge for telecommunications

Online Distinguished Lecture - Applied metrology for novel human-computer interaction

on 12-12-2023

... Brain-computer interfaces (BCIs) are a novel means of human-computer interaction relying on the direct measurement of brain signals. Possible applications consist of replacing, restoring, improving, enhancing, and supplementing the natural outputs of the central nervous system, as well as for brain functions investigation. In considering daily-life constraints, researchers are exploring the possibility of integrating extended reality (XR) and electroencephalography (EEG). Nevertheless, those studies were more application-oriented and they did not deal with a metrological characterization of the stimulation and detection equipment.

In this 1-hour webinar, we will analyse the importance of a metrological characterization in investigating the harmonic components of visually-evoked brain potentials. This will be done by discussing methods for characterizing the different blocks of a neural interface.

Antonio Esposito received his MSc degree in electronic engineering at the University of Naples Federico II (Italy) in 2017 and the Ph.D. in Metrology at Polytechnic of Turin (Italy) in 2022 with a doctoral thesis on “Instrumentation for daily-life brain-computer interfaces: applied metrology for assistive devices relying on steady-state visually evoked potentials and motor imagery”.
He has been working with visually evoked potentials elicited through extended reality glasses and he participated in the development of a prototype for industrial and healthcare applications. Currently, he also investigates neurofeedback for motor imagery-based interfaces in telerehabilitation with a focus on neurodegenerative diseases.
Antonio was designated “Distinguished Lecturer 2023-2025” for the Instrumentation and Measurement Society of IEEE on the topic “Applied metrology for novel human-computer interactions” and he is the Operational Chair of the IEEE MetroXRAINE International Conference.

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Quantum Leap: Exploring the Potential of Quantum Machine Learning for Communication Networks

on 24-11-2023

... Future 6G networks are expected to surpass the advances made in 5G, by providing the faster speeds, lower latency, and extended coverage needed for emerging transformative applications, while at the same time achieving greater energy and spectral efficiency, as well as enhanced security and reliability. While 6G is currently in its initial phases of development and standardization, it is already foreseen to incorporate not just incremental technical enhancements but also pioneering innovations compared to its forerunner, 5G. Indeed, quantum technologies are expected to play an important role in 6G. This goes beyond mechanisms such as quantum key distribution for secure communications; it includes the integration of quantum computing for advanced data processing within 6G networks. As 6G networks are set to integrate artificial intelligence and machine learning even more intrinsically into their operation, the concept of quantum machine learning (QML) emerges as a promising opportunity to enable swift data processing, network optimization, and increased security and privacy. In this presentation, we will look at the fundamentals of quantum computing and quantum machine learning, explore the possibilities they offer for future 6G networks, and the potential for revolutionary advances they offer, while presenting some of the important challenges associated with their integration into 6G networks.

Soumaya Cherkaoui is a Full Professor at the Department of Computer and Software Engineering at Polytechnique Montréal, Canada. From 1999 to 2021, she was a professor at the Department of Electrical and Computer Engineering at the Université de Sherbrooke, Québec, Canada. Before joining academia as a professor in 1999, she worked for industry as a project leader on projects targeted at the Aerospace Industry. Cherkaoui research interests lie in the convergence of communications and artificial intelligence, machine learning in next-generation networks (5G and beyond/6G), Sustainable machine learning, Quantum Machine Learning, Federated Learning and their applications (e.g., autonomous vehicles, smart grid, IoT, industrial IoT). Pr. Cherkaoui has held invited positions at leading institutions including the University of California at Berkeley. Bell Laboratories, Monash University, and the University of Toronto, as well as an adjunct position at Lulea University, in Sweden. Pr. Cherkaoui avails of a long research experience in wireless networking. Her work resulted in technology transfer to companies and to patented technology. She has delivered several keynote addresses and invited talks in the area. Pr. Cherkaoui has published over 200 research papers in reputed journals and conferences. She has been a guest editor and a member of the editorial board of several IEEE, Wiley, and Elsevier Journals including IEEE JSAC, IEEE Network, IEEE Systems and Computer Networks. Her work was awarded with recognitions and best paper awards including the Mirela Notare Award in 2033, the best paper award at IEEE LCN 2021, and a best paper award at IEEE ICC in 2017. She has chaired prestigious conferences such as IEEE LCN 2019 and has served as a symposium co-chair for flagship conferences including IEEE ICC 2018, IEEE Globecom 2018, IEEE Globecom 2015, IEEE ICC 2014, and IEEE PIMRC 2011. She was also Chair of the IEEE Communications Society Technical Committee on IoT-Ad hoc and Sensor Networks. She is a professional engineer in Canada.

This lecture has been integrated into the agenda for National Scientific Culture Day 2023.

The register is mandatory.

November 24, 3:00 p.m. to 4:30 p.m.
Face-to-face: Auditorium Museu dos Lanifícios da UBI, Núcleo Museológico da Real Fábrica Veiga, Caminho do Biribau, Covilhã (Goldra)

For those unable to join in person, you can access the lecture via Zoom using the following link: More Information..