Advisory Board and Editors Artificial Intelligence
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.
Bruno Duarte Gomes
My primary area of research is in brain decoding using machine learning and deep learning, particularly in the context of epilepsy, Parkinson's disease, and cognitive processes in healthy individuals. My research also includes studying human and non-human primates visual system using psychophysics, visual evoked potentials and cortical extracellular recordings.
Education:
Ph.D., Neuroscience and Cell Biology, Federal University of Para
M.Sc., Neuroscience and Cell Biology, Federal University of Para
B.Sc., Biological Sciences, Federal University of Para
Shawn M Gomez
Professor and Associate Chair for Research in the Joint Department of Biomedical Engineering at UNC-CH and NCSU and Professor in the Department of Pharmacology at UNC-CH. Previous Florence Gould Scholar and Pasteur Foundation Fellow. Current research interests in systems and synthetic biology, bioimage informatics, and network science applied to biology. Broader interests in translational medicine and the fostering of innovative solutions to problems in healthcare.
Andrew R Gray
I am a biostatistician in the Biostatistics Centre at the University of Otago, a role I have held since 2004. Most of my work involves collaborating on a wide range of research projects in the health sciences, particularly in paediatric obesity, sleep, and physical activity; respiratory epidemiology, mostly asthma and COPD; dentistry; and health systems. I also work on statistical methods research, mostly topics inspired by these collaborations.
Prior to my current position I was a software metrics and machine learning researcher in the Department of Information Science at the same institution.
Chenghong Gu
Dr Chenghong Gu currently is a Lecturer with the Department of Electronic and Electrical Engineering, University of Bath, Bath, UK. Previously, he was EPSRC Research Fellow with the University of Bath. He received the Master’s degree from the Shanghai Jiao Tong University, Shanghai, China, in 2007 and PhD degree from the University of Bath, U.K, in 2010, both in electrical engineering. His major research interest is in the multi-vector energy system, smart grid planning and operation, power economics and markets. Dr Gu’s research has been supported by UK funding agency (EPSRC), the industry (NPG, NGC, and WPD), and the UK government (DECC). He now is the Subject Editor IET Smart Grid.
Jeonghwan Gwak
Dr. Jeonghwan Gwak received his Ph.D. degree in Machine Learning and Artificial Intelligence from Gwangju Institute of Science and Technology, Gwangju, Korea in 2014. From 2002 to 2007, he worked for several companies and research institutes as a Researcher and a chief technician. From 2014 to 2016, he worked as a Postdoctoral Researcher in GIST, and from 2016 to 2017 as a Research Professor. From 2017 to 2019, he was a Research Professor in Biomedical Research Institute & Department of Radiology at Seoul National University Hospital, Seoul, Korea. From 2019, he joined Korea National University of Transportation (KNUT) as an Assistant Professor and since 2021, he is an Associate Professor. He is the Director of the Algorithmic Machine Intelligence laboratory. His current research interests include deep learning, computer vision, image and video processing, AIoT, fuzzy sets and systems, evolutionary algorithms, optimization, and relevant applications of medical and visual surveillance systems.
Ernst Moritz Hahn
I am assistant professor at the University of Twente in the group FMT working in probabilistic model checking. Previously Lecturer at Queen's University Belfast, Marie-Curie fellow at University of Liverpool, associate professor at Institute of Software, Chinese Academy of Sciences, PostDoc at University of Oxford, PhD at Saarland University.