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.
Jun Ye
Jun Ye is a professor in the School of Civil and Environmental Engineering, Ningbo University, P.R. China. He has more than 30 years of experience in teaching and research. His research interests include soft computing, neutrosophic theory and applications, fuzzy decision making theory and methods, intelligent control, robotics, pattern recognition, medical diagnosis, fault diagnosis, and rock mechanics. He has published more than 300 papers in journals, written a number of books related to his research work, and finished a few projects sponsored by the government of P.R. China. He was selected as “Elsevier Chinese Most Cited Researchers” in 2019, 2020 and 2021. In 2022, he was also selected as the 8th edition of Research.com ranking of top Computer Science scientists.
Andrea Brunello
I am an Assistant Professor (tenure-track) at the Department of Humanities and Cultural Heritage (DIUM) of the University of Udine. In addition, I am part of the Data Science and Automatic Verification Laboratory, at the Department of Mathematics, Computer Science and Physics (DMIF) at the same University. As a figure straddling the two departments, I am part of the board of directors of the AI4CH Initiative, and I am interested in both practical aspects of Artificial Intelligence and philosophical issues. I am and have been a core member of several national and international projects with both institutional and corporate partners, such as u-blox, SAL Silicon Austria Labs, GAP srlu, and beanTech.
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.
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".
Marco Piangerelli
Dr. Marco Piangerelli had his M.Sc. in Bioengineering from the University of Bologna and got his Ph.D. in Computer Science from the University of Camerino, where he is currently a Research Associate. His research interests are mainly on Unsupervised techniques for Machine Learning and Data Science in Manufacturing and Bio Science, Self-Adaptive Systems, and Topological Data Analysis. He is the author of many publications and was a PC member for many conferences and Workshops (AAAI-MAKE 2022-23-24 Spring Symposium, SACAIR 2023, DESRIST 2023, ATDA2019). He co-organized the 9th International Workshop on Engineering Energy Efficient InternetWorked Smart seNsors (E3WSN ) hosted by the 37th International Conference on Advanced Information Networking and Applications (AINA) at the Federal University of Juiz de Fora, Brazil. He has experience in Technological transfer projects and actively collaborates with international companies (INGKA, Schnell S.p.A., Sigma S.p.A., and Nuova Simonelli S.P.A.) and Italian ones (Syeew S.r.l). In 2024, he will be a Visiting Researcher at Addis Ababa University (Ethiopia) to work on topics related to his research fields.
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.
Antonia Lopes
Antónia Lopes is Associate Professor at the University of Lisbon, Portugal, since March 2006. She received a Ph.D. in Informatics at the University of Lisbon in 1999 and holds a BSc and MSc in Applied Mathematics from Technical University of Lisbon. Her research interests are mainly in the area of formal methods for software engineering. These include mathematically based techniques for the specification, modelling and analysis of various types of software intensive systems.
Jingbo Wang
Prof Wang's research spans several disciplines including quantum dynamics theory, quantum computation and information, atomic physics, and computational science. She has published extensively, including a recent book published by Springer, four book chapters, and numerous journal papers. Prof Wang currently leads the quantum dynamics and computation group at The University of Western Australia. She and her research team have developed advanced numerical techniques to solve problems in both quantum and classical domain.
Hemant Rathore
Hemant Rathore received his B.E. and M.E. in computer science from RGTU, India, and BITS Pilani, India, in 2010 and 2013, respectively. He is currently associated to Department of Computer Science and Information Systems at BITS Pilani, India; and has strong academic and industry research experience in the field of security, and currently works in the domain of adversarial learning and explainability in malware detection models based on machine learning and deep learning.
Hemant has published many research papers in various reputed SCI journals and CORE-ranked (A*, A, and B) conferences. He also won the prestigious K Shankar Meritorious Paper Award 2021 in the journal category. Hemant was selected to present his work in the 11 IDRBT Doctoral Colloquium 2021, and he received multiple travel and registration grants from a number of reputed conferences such as NDSS, IEEE INFOCOM, IEEE PerCom, IEEE S & P, IACR Eurocrypt, etc. Hemant has also been invited to various venues (e.g. BDA, TENCON, etc.) for invited tutorials, talks, and seminars.
His teaching credentials include taught courses in the areas of Network Security, Advanced Data Mining, and Data Mining to undergraduate and postgraduate students; in addition to guiding and supervising numerous students in short-term projects.
Hemant is a member of the IEEE and ACM.
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.
Hoang Nguyen
Dr. Hoang Nguyen is a Lecturer (Computational biologist, data scientist, and computer scientist) within the School of Innovation, Design, and Technology at the Wellington Institute of Technology in New Zealand.
His research interests include Applied Data Science, Machine Learning, Deep Learning, Computer-aided Drug Design, Bioinformatics, and Health informatics.
Xianye Ben
Xianye Ben received a Ph.D. degree in pattern recognition and intelligent system from the College of Automation, Harbin Engineering University, Harbin, in 2010. She is currently working as a full Professor in the School of Information Science and Engineering, Shandong University, Qingdao, China. She has published more than 100 papers in major journals and conferences, such as IEEE T-PAMI, IEEE T-IP, IEEE T-CSVT, IEEE T-MM, PR, CVPR, etc. Her current research interests include pattern recognition and image processing. She received the Excellent Doctoral Dissertation award from Harbin Engineering University. She was also enrolled by the Young Scholars Program of Shandong University.