Advisory Board and Editors Artificial Intelligence
Leonilde Varela
The main research interests of Leonilde Varela rely on the Manufacturing Management domain: Production Planning, Control and Optimization and in Collaborative Paradigms, Networks and Decision Making Models, Methods and Tools, and Systems, Web Applications and Services for supporting Engineering and Production Management. She focuses on exploring international scientific collaborations, mainly in terms of joint publications, projects, and special issues proposals, with colleagues from several institutions. She is an active member in the organizing and scientific committees of several internationa conferences and integrates several research networks and organizations, such as: Euro Working Group of Decision Support Systems (EWG-DSS); Institute of Electrical and Electronics Engineers (IEEE); Industrial Engineering Network (IE Network); Institute of Industrial and Systems Engineers (IISE); Machine Intelligence Research Labs, Scientific Network for Innovation and Research Excellence (MirLabs).
Eleni Vasilaki
I am Professor of Bioinspired Machine Learning at the Faculty of Engineering, University of Sheffield and the head the Machine Learning group. Prior to my Academic appointment in Sheffield, I was Scientific Collaborator in the groups of Prof. Wulfram Gerstner at the Ecole Polytechnique Fédérale de Lausanne (EPFL) and Prof. Walter Senn at the University of Bern. I hold a PhD in Computer Science and Artificial Intelligence (University of Sussex), a Masters in Microelectronics (University of Athens) and a Bachelors degree (with distinction) in Informatics & Telecommunications (University of Athens). I am a Chartered Engineer, registered with the Engineering Council UK in membership of the Institution of Engineering and Technology.
Shravan Vasishth
Professor of Psycholinguistics at the Department of Linguistics, University of Potsdam, Germany. Specialization in computational models of sentence comprehension; sentence processing in aphasia; working memory and language comprehension; Bayesian statistics.
Chaman Verma
Dr. Chaman Verma is an Assistant Professor at the Department of Media and Educational Informatics, Faculty of Informatics, Eötvös Loránd University. He is also the project leader and chief researcher of his project sponsored by National Research, Development and Innovation (NRDI) Hungary. He also won a young educator scholarship for novel research sponsored by the EKÖP, NRDI Fund, and the Hungarian Government.
He pursued a post-doctorate at the Faculty of Informatics, Eötvös Loránd University, Budapest, Hungary, sponsored by UNKP, MIT (Ministry of Innovation and Technology), the National Research, Development and Innovation (NRDI) Fund, and the Hungarian Government. He received a Ph.D. in informatics from the Doctoral School of Informatics, Eötvös Loránd University, Budapest, Hungary, with the Stipendium Hungaricum Scholarship funded by the Tempus Public Foundation, Government of Hungary. During his Ph.D., he won the EFOP Scholarship, co-founded by the European Union Social Fund and the Government of Hungary, as a professional research assistant in a real-time system from 2018 to 2021. He also received the Stipendium Hungaricum Dissertation Scholarship of Tempus Public Foundation, Government of Hungary, from 2021 to 2022.
He has been awarded several Erasmus Scholarships for conducting international research and academic collaboration with European and non-European universities. He received the best scientific publication award from the Faculty of Informatics, Eötvös Loránd University, Budapest, Hungary, In the years 2021-2024. He has also been awarded the ÚNKP scholarship for research by the Ministry of Innovation and Technology and the National Research, Development and Innovation (NRDIO) Fund, Government of Hungary, 2021-2023.
He has around ten years of experience in teaching and industry. He has over 150 scientific publications in the IEEE, Elsevier, Springer, IOP Science, Walter de Gruyter and MDPI. His research interests include data analytics, feature engineering, real-time systems, and educational informatics. He is a life member of ISTE, New Delhi, India. He is a member of the editorial board and a reviewer of various international journals and scientific conferences. He was the leading guest editor of the special issue Advancement in Machine Learning and Applications in Mathematics, IF- 2.25, MDPI, Basel, Switzerland, in 2022. He was also a guest editor in two Springer journals. He is a co-editor in the series of conference proceedings of ICRIC-2021-24 published by Springer, Singapore. He reviews many scientific journals, including IEEE, Springer, Elsevier, Wiley, and MDPI. He has Scopus citations of 1603 with an H-index of 24. He has Web of Science citations of 355 with an H-index of 13.
Ankit Vishnoi
Dr. Ankit Vishnoi is an Associate Professor in the Department of Computer Science & Engineering at Graphic Era (Deemed to be) University, Dehradun, India. With more than two decades of combined academic and industry experience, he has established himself as a leading researcher in cybersecurity, artificial intelligence, IoT ecosystems, and advanced healthcare analytics. Prior to his academic career, he worked with IBM India Pvt. Ltd., contributing to large-scale enterprise solutions and gaining extensive expertise in applied machine learning and secure systems design.
Dr. Vishnoi has published over 30 peer-reviewed research papers in reputed journals and international conferences and has served in key leadership roles for multiple IEEE, Springer, and EAI conferences, including Convener, Co-Convener, Organizing Secretary, and Track Chair. He is actively involved in editorial and review responsibilities for several Scopus-indexed and SCI journals.
His current research focuses on AI-driven cybersecurity frameworks, deep learning for medical imaging, smart contract vulnerability detection, and human–computer interaction models. He also mentors research scholars across emerging domains and contributes to interdisciplinary innovation and technology-driven community development initiatives.
Stefan Wagner
Stefan Wagner is full professor of software engineering at the Technical University of Munich in the TUM School of Communications, Information and Technology. He studied computer science in Augsburg and Edinburgh and psychology in Hagen. He holds a doctoral degree in computer science from TU Munich, where he also worked as a post-doc. Previously, he was a full professor at the University of Stuttgart. His main research interests are empirical studies, software quality, human factors, AI-assisted software engineering, AI-based software and automotive software. He is a member of GI and a senior member of ACM and IEEE.
Shibiao Wan
Dr. Shibiao Wan is currently an Assistant Professor in the Department of Genetics, Cell Biology and Anatomy, and the Co-Director for the Bioinformatics and Systems Biology (BISB) PhD Program at University of Nebraska Medical Center (UNMC). He is also an Assistant Professor (courtesy) in the Department of Biostatistics at UNMC.
With more than 15 years of experience in machine learning, bioinformatics, and computational biology, Dr. Wan has published >60 articles in top-tiered journals such as Genome Research, Nature Communications, Science Advances, Circulation Research, Briefings in Bioinformatics, and Bioinformatics. Dr. Wan is the Editor-in-Chief for Current Proteomics, and an Associate Editor/Academic Editor/Editorial Board Member for a series of prestigious journals such as Briefings in Functional Genomics, Heliyon, BMC Bioinformatics, International Journal of Microbiology, PeerJ Computer Science, BioMed Research International, and Computational and Mathematical Methods, and a guest associate editor for multiple high-impact journals.
He is a Scientific Program Committee (SPC) member for American Medical Informatics Association (AMIA) Annual Symposium and a Technical Program Committee (TPC) member for >20 machine learning related international conferences including IEEE ICTAI. Dr. Wan is also a reviewer for >70 prestigious journals including Nature Biotechnology, Nature Methods, Nature Communications, Nature Computational Science, Science Advances, Nucleic Acids Research, Advanced Science, Cancer Research, Genome Biology, and Genome Medicine. Dr. Wan has received a number of accolades including the Springer Nature Editor of Distinction Award in 2025 by Springer Nature, the New Investigator Award in 2024 by UNMC, the FIRST Award in 2023 by Nebraska EPSCoR, the Outstanding Young Alumni Award in 2022 by HK PolyU as well as the Global Peer Review Awards (top 1%) in “Cross-Field” and “Biology and Biochemistry” in 2019 by Clarivate. Dr. Wan is a member of AACR, AMIA, ISCB and ACM and an IEEE Senior Member.
Kezhi Wang
Kezhi Wang received his Ph.D. degree from the University of Warwick, U.K. He was a Senior Research Officer in University of Essex, U.K. Currently He is a Senior Lecturer with Department of Computer Science, Brunel University, U.K.
Dapeng Wang
Dr Dapeng Wang is a Senior Bioinformatician in Integrative Analysis at the COMBAT consortium at the University of Oxford using multi-omics techniques in combination with the cutting-edge bioinformatic approaches and statistical methods to explore the pathogenesis of COVID-19 and stratification of patients as well as inform the treatment strategy based on genomics information.
Dr Wang received a bachelor’s degree in mathematics from the Shandong University in 2006 and obtained a PhD degree in bioinformatics from the Beijing Institute of Genomics of the Chinese Academy of Sciences in 2011. After his graduation, he continued to conduct research at the same institute from 2011 to 2014 and afterwards moved to the UK to take up various roles at the Cancer Institute at the University College London (2014-2016), the Department of Plant Sciences at the University of Oxford (2016-2018) and the LeedsOmics at the University of Leeds (2018-2020).
Shuihua Wang
Shuihua Wang received her B.S. Degree in information science and engineering from Southeast University in Nanjing, China, in 2008; the M. S. degree in Electrical Engineering from the City College of New York, USA in 2012, and the Ph. D degree in Electrical Engineering from Nanjing University, Nanjing, China, in 2017. She visited Kyushu Institute of Technology in 2017. From 2013 to 2018 she joined Nanjing Normal University, and worked as an assistant professor. From 2018-2019, she served in Loughborough University. She is now working as a research associate at the University of Leicester. Her research interests focus on Machine learning, Deep learning, biomedical image processing. She has published over 30 papers in peer-reviewed international journals and conferences in these research areas. She was serving as a professional reviewer for many well-reputed journals and conferences including IEEE Transactions on Neural Networks and Learning Systems, Neuron Computing, Pattern recognition, scientific reports, and so on. She is currently serving as Guest Editor-in-Chief of Multimedia Systems and Applications, Associate editor of Journal of Alzheimer’s Disease and IEEE Access. She is a member of the IEEE.
Jingzhe Wang
Jingzhe Wang received his Ph. D in Cartography and Geographic Information System from Xinjiang University, Urumqi, China, in 2019. He is now working as a research associate at MNR Key Laboratory for Geo-Environmental Monitoring of Great Bay Area, Shenzhen University. His research interests focus on Earth observation and remote sensing, spectral modeling, quantitative estimation of soil properties, digital soil mapping, GIS, spatial analysis, and environmental sustainability. He has published over 60 papers in peer-reviewed international journals in these related research areas and has served as a reviewer for many journals and conferences including Remote Sensing of Environment, Ecological Indicators, Computers and Electronics in Agriculture.
Janet Wiles
Professor of Complex and Intelligent Systems at the University of Queensland.