KEYNOTE SPEAKERS keyboard_voice

Speaker: Prof. Carlo Sansone

University of Naples Federico II, Italy

Due to unforeseen circumstances, the keynote speaker has been changed from Dr. Sung to Prof. Sansone.

Biography

Carlo Sansone is full professor of Computer Engineering at the Department of Electrical Engineering and Information Technology of the University of Naples Federico II, where he coordinates the Master in Human-Centred Artificial Intelligence.
He is the author of more than 300 papers in international journals and conference proceedings. His research interests cover the areas of image analysis and recognition, machine learning and deep learning. From an application perspective, his main contributions have been in the fields of biomedical image analysis, biometrics, intrusion detection in computer networks and image forensics. He has coordinated projects in the fields of biomedical image interpretation, network intrusion detection and cyberbullying detection using artificial intelligence techniques.

Prof. Sansone is a Fellow of the IAPR (International Association for Pattern Recognition), the AAIA (Asia-Pacific Artificial Intelligence Association) and the AIIA (International Artificial Intelligence Industry Alliance). He is also Director of the National Laboratory of Artificial Intelligence and Intelligent Systems (AIIS) of the CINI consortium and Vice President of the FAIR (Future Artificial Intelligence Research) foundation.

Title: Resilient AI in the medical domain

Abstract

The challenges posed by Human-Centered AI and Human-AI interaction, that are at the basis of a multiplicity of applications share a crucial aspect: the use of machine learning algorithms trained with real-world data that are unstructured, noisy, often incomplete/limited in number, and partially inconsistent. To achieve adequate performance, it is necessary to develop specific AI methodologies for processing this data, making AI performance resilient and robust in these contexts. This talk will present some techniques to enhance AI algorithm resilience to these challenges, with a focus on applications in the medical domain.

Speaker: Prof. Andrea Cavallaro

EPFL, Switzerland

Biography

Andrea Cavallaro is the Idiap Director and a Full Professor at EPFL. He is a Fellow of the Higher Education Academy, a Fellow of the International Association for Pattern Recognition, and an ELLIS Fellow. His research interests include machine learning for multimodal perception, computer vision, machine listening, and information privacy.
Andrea received his PhD in Electrical Engineering from EPFL in 2002. He was a Research Fellow with British Telecommunications in 2004 and was awarded the Royal Academy of Engineering Teaching Prize in 2007; three student paper awards on target tracking and perceptually sensitive coding at IEEE ICASSP in 2005, 2007 and 2009; and the best paper award at IEEE AVSS 2009. In 2010, he was promoted to Full Professor at Queen Mary University of London, where he was the founding Director of the Centre for Intelligent Sensing and the Director of Research of the School of Electronic Engineering and Computer Science. He was a Turing Fellow (2018-2023) at The Alan Turing Institute, the UK National Institute for Data Science and Artificial Intelligence.

He was selected as IEEE Signal Processing Society Distinguished Lecturer (2020-2021) and served as Chair of the IEEE Image, Video, and Multidimensional Signal Processing Technical Committee (2020-2021). He also served as member of the Technical Directions Board of the IEEE Signal Processing Society and as elected member of the IEEE Multimedia Signal Processing Technical Committee and chair of the Awards committee of the IEEE Signal Processing Society, Image, Video, and Multidimensional Signal Processing Technical Committee.
He served as Senior Area Editor for the IEEE Transactions on Image Processing and as Editor-in-Chief of Signal Processing: Image Communication (2020-2023); as Area Editor for the IEEE Signal Processing Magazine (2012-2014); and as Associate Editor for the IEEE Transactions on Image Processing (2011-2015), IEEE Transactions on Signal Processing (2009-2011), IEEE Transactions on Multimedia (2009-2010), IEEE Signal Processing Magazine (2008-2011) and IEEE Multimedia (2016-2018). He also served as Guest Editor the IEEE Transactions on Multimedia (2019), IEEE Transactions on Circuits and Systems for Video Technology (2017, 2011), Pattern Recognition Letters (2016), IEEE Transactions on Information Forensics and Security (2013), International Journal of Computer Vision (2011), IEEE Signal Processing Magazine (2010), Computer Vision and Image Understanding (2010), Annals of the British Machine Vision Association (2010), Journal of Image and Video Processing (2010, 2008), and Journal on Signal, Image and Video Processing (2007).
He published a monograph on Video tracking (2011, Wiley) and three edited books: Multi-camera networks (2009, Elsevier); Analysis, retrieval and delivery of multimedia content (2012, Springer); and Intelligent multimedia surveillance (2013, Springer).

Title: The Pursuit of Privacy in the AI Age

Abstract

We generate and share vast amounts of data that reveal a detailed portrait of our lives, exposing our identity, behaviors, and preferences. To enable individuals to exercise greater control over their personal information, I will present novel approaches to identify and protect sensitive attributes within data. I will present feature representations that effectively disentangle sensitive information from non-sensitive attributes. Furthermore, I will present perturbation techniques designed to obfuscate sensitive attributes while preserving or potentially enhancing the overall quality of the data, thereby safeguarding sensitive information from unwanted inference.