Advisory Board and Editors Artificial Intelligence
Luigi Di Biasi
Luigi Di Biasi is a Researcher in the Department of Computer Science at the University of Salerno.
Since 2023, he has been a Deferred Tenured Teacher for the A041 STEM class at ITT Maria Curie – Naples (NATF190001).
He earned his Bachelor’s degree in Computer Science from the University of Salerno in 2010 and his Master’s degree in Computer Science in 2014. In 2023, he completed his PhD in Computer Science at the same university.
Starting from the 2023/24 academic year, he has been a lecturer and co-instructor for courses on Databases, Statistics, and Data Analysis.
Antonio Jesus Diaz-Honrubia
Antonio J. Díaz-Honrubia is an Associate Professor at Universidad Politécnica de Madrid, to which he joined after holding an Assistant Professorship at Universidad de Oviedo and a part time Professorship at Universidad de Castilla-La Mancha (a job that he combined with a position in the R&D department of a private company in the telecommunications field).
He received his Ph.D. in 2016 from the Universidad de Castilla-La Mancha, where he had also received his B.Sc. (Spanish National Extraordinary Award) and M.Sc. in Computer Science and Engineering.
His research interests include video transcoding, perceptual video coding, multimedia standards, scalable video coding, and simultaneous video coding. More recently, he is moving forward to the topic of data analysis and validation.
He has been a visiting researcher at Ghent University (Belgium) for 4 months, the Florida Atlantic University (USA) for 3 months, and the Technische Informationsbibliothek (TIB) (Germany) for 6 months.
He has more than 30 publications in these areas in international refereed journals and conference proceedings.
Trang Do
Dr. Trang Do earned her PhD degree from the National University of Singapore in 2013. She is a proactive and motivated educator and data scientist, showcasing a track record of effectively managing expansive and intricate projects alongside engagements with stakeholders and government agencies. Her expertise spans data and computer science, coupled with a foundation in economics and bioinformatics, driving an ongoing pursuit of professional development. Her research interests encompass a wide scope within data science, intelligent systems, and interdisciplinary computing. Presently, her primary focus centers on machine learning, deep learning, explainable AI, data analysis, and visualization, particularly within the realms of health informatics, drug discovery, bioinformatics, tourism, and intelligent systems.
Juan Pedro Dominguez-Morales
Prof. Juan Pedro Dominguez-Morales was born in Sevilla (Sevilla, Spain) in 1992. He received the B.S. degree in computer engineering, the M.S. degree in computer engineering and networks, and the Ph.D. degree in computer engineering (specializing in neuromorphic audio processing and spiking neural networks) from the University of Seville, in 2014, 2015 and 2018, respectively. His Ph.D. was granted with a research grant from the Spanish Ministry of Education and Science. Since January 2019, he has been working as Assistant Professor in the same university. He is member of the Robotics and Technology of Computers Lab since 2015. His research interests include neuromorphic engineering, spiking neural networks, audio processing and deep learning. He has been an IEEE member for four years.
Ahmed Elazab
Ahmed Elazab received his Ph.D. degree in pattern recognition and intelligent systems from Shenzhen Institutes of Advanced Technology, University of Chinese Academy of Sciences, China, Jan 2017. He was a postdoctoral research fellow from Jan 2018 to April 2020 at the School of Biomedical Engineering, Shenzhen University, Shenzhen, China where he is currently a research associate since Jan 2021. Dr. Elazab has authored and co-authored more than 80 peer-reviewed papers and has been a reviewer in prestigious peer-reviewed international journals. His main research interests include machine and deep learning, medical image analysis, brain anatomy analysis, and computer-aided detection and diagnosis.
Charles P. Elkan
Professor of computer science at the University of California, San Diego, and also Amazon Fellow.
Carlos Fernandez-Lozano
Dr. Carlos Fernandez-Lozano is an Associate Professor at the University of A Coruña (UDC). He is a biomedical data scientist with a deep interest in discovering the complex relationships between different biological levels. His research track is multidisciplinary as he is trained in computer science, machine learning, bioinformatics, and biostatistics. His research line is focused on how biological interactions are manifested at the disease level through the use, development, and application of kernel-based computational approaches that integrate different levels of biological data on the microorganism, gene, protein, and medical imaging axis.
Simone Fontana
Prof. Simone Fontana is an assistant professor at Università degli Studi di Milano - Bicocca.
His main research activity is in the field of 3D robot perception, with special attention to point clouds registration, a problem for which he has developed a benchmark. More recently, Dr. Fontana's research has focused on the use of informatics techniques for neuropsicology and neuroscience.
He is a co-investigator of the DriveWin project, which aims to investigate the effects of different types of non-invasive neurostimulation on attention while driving. Attention was assessed on a driving simulator and two age groups were compared.
Prof. Fontana is also a lecturer at the School of Law and at the Advanced Specialization School in Neuropsychology.
Tarek Gaber
Tarek Gaber is a Senior Lecturer (Associate Professor) at the University of Salford (UK) and a Full Professor of Computer Science at Suez Canal University (Egypt). He has over two decades of academic and research experience across cybersecurity, artificial intelligence (AI), secure systems, and Safe AI. His work focuses on developing resilient AI models, secure digital infrastructures, and innovative applications for industry and public sector transformation. Dr. Gaber has authored over 100 scholarly publications, including journal articles, conference papers, book chapters, and edited volumes — with more than 40 published in Q1 journals. He has led or co-led research projects exceeding £6 million in funding, supported by Innovate UK, UKRI, Research England, and UKAEA. His research excellence has earned him recognition among Stanford University’s top 2% of scientists globally. He has served as Programme Leader for the MSc Cyber Security programme at Salford, contributed to several Knowledge Transfer Partnerships (KTPs), and engaged in interdisciplinary projects with SMEs to deploy secure and explainable AI solutions. Dr. Gaber is a Fellow of the UK Higher Education Academy (FHEA), a member of IEEE, and frequently serves as a keynote speaker, journal reviewer, and editorial board member in his field.
Hemant Ghayvat
I am an Associate Professor at Linnaeus University, where my research and teaching center on AI-enabled systems for healthcare and smart environments. My work leverages the power of IoT, machine learning, and deep learning to create practical solutions, from contactless heart monitoring to smart home technologies that support assisted living. I am passionate about using technology to improve well-being and create more intelligent, responsive environments.
Chiara Ghidini
Chiara Ghidini is a senior Research Scientist at Fondazione Bruno Kessler (FBK), Trento, Italy, where she heads the Process & Data Intelligence (PDI) research unit. She obtained her PhD in Computer Science Engineering in a joint programme between the Università “La Sapienza” of Rome and the University of Trento.
Her scientific work in the areas of Semantic Web, Knowledge Engineering and Representation, Multi-Agent Systems and Process Mining is internationally well known and recognised, and she has made significant scientific contributions in the areas of: formal semantics for contextual reasoning and multi-context logics; formal frameworks for the specification of deliberative resource bounded agents; ontology mappings and integration; collaborative modeling platforms, and predictive business process monitoring.
Dr. Ghidini has actively been involved in the organisation of several workshops and conferences on multiagent systems, Contexts-based representations, Knowledge Engineering, and Semantic Web, and has served as programme committee member for most of the top international conferences in these areas.
She has been involved in a number of international research projects, among which the FP7 Organic.Lingua and SO-PC-Pro European projects, a well as industrial projects in collaboration with companies in the Trentino area.
Yolanda Gil
Dr. Yolanda Gil is Director of Knowledge Technologies and Associate Division Director at the Information Sciences Institute of the University of Southern California, and Research Professor in Computer Science and in Spatial Sciences. She is also Associate Director of Interdisciplinary Programs in Informatics. She received her M.S. and Ph. D. degrees in Computer Science from Carnegie Mellon University, with a focus on artificial intelligence. Her research is on intelligent interfaces for knowledge capture and discovery, which she investigates in a variety of projects concerning knowledge-based planning and problem solving, information analysis and assessment of trust, semantic annotation and metadata, and community-wide development of knowledge bases. Dr. Gil collaborates with scientists in different domains on semantic workflows and metadata capture, social knowledge collection, computer-mediated collaboration, and automated discovery. Dr. Gil has served in the Advisory Committee of the Computer Science and Engineering Directorate of the National Science Foundation. She initiated and chaired the W3C Provenance Group that led to a community standard in this area. Dr. Gil is a Fellow of the Association for Computing Machinery (ACM), and Past Chair of its Special Interest Group in Artificial Intelligence. She is also Fellow of the Association for the Advancement of Artificial Intelligence (AAAI), and was elected as its 24th President in 2016.