Academic Editors
The following people constitute the Editorial Board of Academic Editors for PeerJ Computer Science. These active academics are the Editors who seek peer reviewers, evaluate their responses, and make editorial decisions on each submission to the journal. Learn more about becoming an Editor.
Silvio Peroni
I hold a Ph.D. degree in Computer Science and I am an Associate Professor at the Department of Classical Philology and Italian Studies, University of Bologna, where I teach 'Basic Informatics' and 'Computational Thinking and Programming'.
I am an expert in document markup and semantic descriptions of bibliographic entities using OWL ontologies. I am one of the main developers of the SPAR (Semantic Publishing and Referencing) Ontologies, Co-Director of OpenCitations, and founding member of the Initiative for Open Citations (I4OC).
I am an Editorial Board member of Data Science, PeerJ Computer Science, and I am member of the Digital Humanities Advanced Research Centre (/DH.arc), part of the Advisory Board of DBLP and Qeios, Ambassador of Figshare and PeerJ, and member of the Association for Computing Machinery, of the International Society for Scientometrics and Informetrics, and of the Associazione per l’Informatica Umanistica e la Cultura Digitale.
Among my research interests are Semantic Web technologies, markup languages for complex documents, design patterns for digital documents and ontology modelling, and automatic processes of analysis and segmentation of documents. In particular, my recent works concern the empirical analysis of the nature of scholarly citations, bibliometrics and scientometrics studies, visualisation and browsing interfaces for semantic data, and the development of ontologies to manage, integrate and query bibliographic information.
Vijay Mago
Vijay Mago received a Ph.D. degree in computer science from Panjab University, India, in 2010. In 2011, he joined the Modeling of Complex Social Systems Program at The IRMACS Centre, Simon Fraser University. He is currently the Chair and an Associate Professor with the Department of Computer Science, Lakehead University, Thunder Bay, ON, Canada, where he teaches and conducts research in areas, including big data analytics, machine learning, natural language processing, artificial intelligence, medical decision making, and Bayesian intelligence. He has published extensively on new methodologies based on soft computing and artificial intelligence techniques to tackle complex systemic problems, such as homelessness, obesity, and crime. He serves as an Associate Editor for IEEE Access and BMC Medical Informatics and Decision Making.
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.
Charles P. Elkan
Professor of computer science at the University of California, San Diego, and also Amazon Fellow.
Irfan Ahmad
Dr. Irfan Ahmad is an Associate Professor in Information and Computer Science department at King Fahd University of Petroleum and Minerals (KFUPM), Dhahran, Saudi Arabia. He received his PhD in Computer Science from TU Dortmund, Germany in 2017.
Dr. Ahmad's research interests are in the areas of pattern recognition especially in document-image analysis, handwriting recognition, and machine-printed text recognition. In addition, he is also interested in machine learning and its applications including deep learning and natural language processing (NLP).
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.
Martina Iammarino
Martina Iammarino is a Tenured Assistant Professor at the Department of Computer Science and Technologies at Pegaso University in Naples.
She holds a Laurea degree in Computer Engineering in 2019 and a PhD degree in Information Technology for Engineering from the University of Sannio in 2023.
Her research focuses on software engineering, data quality, and process engineering, with a growing emphasis on artificial intelligence. Specifically, her work in AI has been pivotal in addressing challenges in the medical field, with a special interest in Parkinson's disease. Through the application of machine learning and deep learning techniques, her research has advanced understanding and innovation in diagnosing, monitoring, and managing this neurodegenerative disorder.
She has published extensively on AI methodologies applied in various domains and has contributed to the AI and healthcare research community as a reviewer for several international conferences and journals.
In addition to serving on the program committee of several international conferences, Martina Iammarino is an Editorial Board Member for the journal Peerj, and is also one of the main organizers of the CISE Workshop "Computational Intelligence and Software Engineering" held at PROFES 2023.
Markus Endler
Markus Endler obtained his Dr. rer. nat. in Computer Science from the Technical University of Berlin (1992), and the Professor Livre-docente title (Habilitation) from the University of São Paulo (2001). From 1989 to 1993 he worked as a researcher at the GMD Research Institute Karlsruhe (Germany), and from 1994 to 2000 as an Assistant Professor at the Institute of Mathematics and Statistics of the University of São Paulo (USP). In 2001 he joined the Department of Informatics of the Pontifícia Universidade Católica in Rio de Janeiro (PUC-Rio), where he is currently Associate Professor. His main research interests include Mobile and Pervasive Computing, IoT Middleware Architectures. Distributed Algorithms for Cooperation and Consensus, Online Data Analytics, and Data Stream Processing. As of 2020, he has supervised 13 PhD thesis and 30+ M.Sc. dissertations.
Álvar Arnaiz-González
Dr. Álvar Arnaiz-González is an Associate Professor within the Department of Computer Science at the University of Burgos.
His main research interests include Machine Learning, Data Mining, ensemble classifiers and instance selection.
Juan A Lara
Juan A. Lara is Associate Professor and Research Scientist at University of Córdoba, Spain. He is currently member of Department of Computer. He holds a Ph.D. in Computer Science and two Post Graduate Masters in Information Technologies and Emerging Technologies to Develop Complex Software Systems from Technical University of Madrid, Spain. He is author of more than a 40 papers published in international impact journals. His research interests in computer science include data mining, knowledge discovery in databases, data fusion, artificial intelligence and e-learning.
Huiyu Zhou
Prof. Huiyu (Joe) Zhou received a Bachelor of Engineering degree in Radio Technology from Huazhong University of Science and Technology of China and a Master of Science degree in Biomedical Engineering from University of Dundee of United Kingdom, respectively. He was awarded a Doctor of Philosophy degree in Computer Vision from Heriot-Watt University, Edinburgh, United Kingdom.
Prof. Zhou currently heads the Applied Algorithms and AI (AAAI) Theme and leads the Biomedical Image Processing Lab at University of Leicester. He was the Director of MSc Programme (2018-19), and currently is the Coordinator of MSc Distance Learning and a Member of Research Committee at School of Informatics. Prior to this appointment, he worked as a Lecturer (2012-17) at the School of Electronics, Electrical Engineering and Computer Science, Queen's University Belfast.
Prof. Zhou has published widely in the field. He was the recipient of "CVIU 2012 Most Cited Paper Award", "MIUA 2020 Best Paper Award", "ICPRAM 2016 Best Paper Award in the Area of Applications" and was shortlisted for "ICPRAM 2017 Best Student Paper Award" and "MBEC 2006 Nightingale Prize".
Kok Yew Ng
I received the BEng (Hons) in Electrical and Computer Systems Engineering and the Ph.D. in Fault Diagnosis and Control Systems from Monash University in 2006 and 2009, respectively. I am currently a Reader in Mechatronics Engineering and Control at the School of Engineering, Ulster University, UK, and I am attached to the Engineering Research Institute.
My research interests include fault diagnosis, mathematical modelling, digital twin, and data analytics for anomaly detection and classification.
In 2014–2015, I was a postdoctoral researcher at the Division of Vehicular Systems, Linköping University, Sweden, where I worked with Volvo Car Corporation (VCC) on advanced fault diagnosis schemes in vehicular engines using model-based and data-driven methods. For this research, I was instrumental in developing a Digital Twin/Simulation Testbed on the MATLAB/Simulink platform for realistic simulation and testing of residuals generation and fault diagnosis methods. This research work was published in the IEEE Control Systems Magazine and the Digital Twin/Simulation Testbed can be downloaded via the main hosting site or its mirror at Linköping University.
Throughout my career, I have secured more than £6.5 million in research grants from various funders such as the Engineering and Physical Sciences Research Council (EPSRC), UK Research and Innovation (UKRI), Global Challenges Research Fund (GCRF), and the Northern Ireland Department for the Economy in the UK; the Fundamental Research Grant Scheme (FRGS), Exploratory Research Grant Scheme (ERGS), and EScienceFund from the Ministry of Higher Education in Malaysia; and industries such as Volvo Car Corporation in Gothenburg, Sweden.
Overall, I have successfully supervised no less than 2 postdoctorals, 8 PhD, and 3 Master’s by Research candidates.
I am also currently attached to the Digital Catapult as an awardee of the EPSRC Innovation Launchpad Network+ (ILN+) Researcher in Residence Scheme. This research project aims to develop an energy mapping Digital Twin technology that contributes towards net zero in wind turbine energy. This technology encompasses the entire energy lifecycle, from mining through storage to utilisation in Northern Ireland (NI). This project also involves collaboration with the Offshore Renewable Energy Catapult.
Other highlights include being a co-investigator in SAFEWATER, a £5 million project funded by UKRI-GCRF, where I led the development and the optimisation of embedded algorithms to control low-cost water disinfection technologies used in the rural areas in South America.
In addition, during the COVID-19 pandemic, I led the Modelling and Forecast Task Force at Ulster where we worked with the Southern Health and Social Care Trust to provide analysis to the Government Specialist Modelling Response Expert Group (SMREG) in Northern Ireland. The main purpose of the project was to validate and inform the SMREG as well as help governing bodies in Northern Ireland to better plan for intervention measures and ultimately flatten the curve. I was also a member of the COVID-19 Task Force set up by the IEEE Region 8 community. In addition, I led a team of researchers and data scientists from Ulster and Queen’s University Belfast to work with the Incident Controller for the State Health Incident Control Centre and Deputy Chief Health Officer of the Department of Health in Western Australia to model the outbreak of COVID-19 on commercial cargo vessels.
I am a Senior Member of the IEEE and I am currently the Vice-Chair of the IEEE Control Systems Society (CSS), UK and Ireland Chapter.
I am the Moderator for the IEEE TechRxiv, the Associate Editor for IEEE Access, Editor for PeerJ Computer Science, and Section Editor for Sage Science Progress.
I am also an Adjunct Senior Research Fellow with Monash University Malaysia where I served as a Lecturer from 2009, and subsequently as Senior Lecturer till 2017.