Valerio Guarrasi graduated with honors in Data Science from Sapienza University of Rome, Italy, where he also completed his PhD in Data Science. He subsequently undertook a PostDoc focusing on Artificial Intelligence for precision medicine at the University Campus Bio-Medico of Rome on the topic of Artificial Intelligence. Currently, he is an Assistant Professor (RTDA) at the same university. His research interests encompass multimodal deep learning, explainable artificial intelligence, and the application of digital twins in biomedical fields.

Agma J. Machado Traina is a Full Professor with the Department of Computer Science of the Mathematics and Computer Science Institute - University of São Paulo (ICMC-USP) since 2008. She holds a Bachelor degree in Computer Science from the ICMC-USP (1983), a Master degree in Computer Science and Computational Mathematics from the ICMC-USP (1987), and a PhD in Computational Applied Physics from the IFQSC-USP (1991). She also spent a sabbatical leave as a visiting researcher at the Computer Science Department of the Carnegie Mellon University (1998-2000) working on Multimedia Databases. She participated in and coordinated several national and international projects, integrating multidisciplinary teams of researchers and students. She has published more than 260 papers in selective journals and conferences, where she has received several awards for best paper, as well as mentored more than 50 graduate students. She participates in several editorial committees of journals and steering committees of conferences in her field. Her research interests include indexing and retrieval of image data by content, similarity queries, data visualization, visual data mining.  Agma has been working in the integration of the results of her research lines with applications for the areas of medicine and agro-climatology, aimed at the development of applied computational systems.

Rosa Sicilia graduated with honours in Biomedical Engineering at Università Campus Bio-Medico (UCBM), where she also completed her PhD in Biomedical Engineering (Computer Science area). After one year as a Post Doc researcher, Rosa is currently Assistant professor (RTDA) at UCBM. Her main research interests are in the machine learning and multimodal data mining fields i.e. she works on radiomics and radiopathomics, Hospital 4.0, eXplainable AI, social networks analysis and on multivariate time series analysis. In 2022 Rosa participated as Programme Committee (PC) Chair in the IEEE 35th International Symposium on Computer Based Medical Systems (CBMS), she was General Chair in the 2023 CBMS edition and she is currently Vice-Chair of CBMS Steering Committee and PC Chair of CBMS 2024. 

Pietro Liò is a Full Professor in the Department of Computer Science and Technology at the University of Cambridge, where he is also a member of the Artificial Intelligence group. His research is primarily centered on the development of Artificial Intelligence models applied to many sectors of science and Mathematics such as: physics, biology, chemistry, and medicine. His current focus is on Graph Neural Network modeling. Prof. Lio' boasts an impressive academic background, holding a Master of Arts degree from Cambridge, along with two PhDs. One is in Complex Systems and Non-Linear Dynamics, earned from the School of Informatics, Department of Engineering at the University of Firenze, Italy. The other is in Theoretical Genetics, awarded by the University of Pavia, Italy.

Federico Siciliano is a PostDoc in Data Science at Sapienza University of Rome. His research interests include Foundations of Deep Learning, Information Retrieval and Explainable Artificial Intelligence, also applied to also applied to Fluorophore Separation & Cancer Outcome Prediction. He is part of the RSTLess research group at Sapienza University of Rome, which focuses on Robust, Safe and Transparent Deep Learning. Prior to this, he completed his Master’s Degree in Data Science at Sapienza University of Rome.