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.
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.
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.
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.
Chintan Amrit
Chintan Amrit is an Associate Professor at the Department of Business Analytics, at the University of Amsterdam. He has completed his PhD from the University of Twente in the area of Coordination in Software Development, having started it at RSM Erasmus University. He holds a master’s degree in Computer Science from the Indian Institute of Science, Bangalore. In the past, he has worked for three years as a software engineer. His research interests are in the area of business intelligence (using machine learning), open-source development and mining software repositories and applying analytics in projects that focus on the UN’s sustainable development goals. He serves as a department editor of IEEE Transactions in Engineering Management, coordinating editor of Information Systems Frontiers journal, an associate editor of PeerJ CS journal, and is a regular track chair at ECIS.
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.
M Murugappan
Prof. Dr. M. Murugappan is currently a Full Professor of Electronics and Communication Engineering at Kuwait College of Science and Technology (KCST), Kuwait. In India, Malaysia, and Kuwait, he taught and conducted research for more than 15 years. Stanford University researchers ranked him in the top 2-percent of scientists worldwide in 2020, 2021, and 2022 for Experimental Psychology, Artificial Intelligence, and Cognitive Neuroscience.
He has authored 70 articles in SCI/SCOPUS journals, 58 conference proceedings, seven book chapters, and edited eight books. Google Scholar records a maximum score of 5654+ citations, along with an H index of 37 and an i10 score of 81 (Ref: Google Scholar). He has been awarded nearly $2.5M for his research by the Malaysian government and the Kuwait Foundation for the Advancement of Sciences (KFAS).
Prof. Murugappan is a member of professional international societies such as IEEE, IET, IACSIT, IAENG, IEI and a Charted Engineer (C.Eng). He has given expert talks in Affective Computing, Artificial Intelligence in Healthcare, and Affective Neuroscience. He is currently the IEEE Kuwait Section's Chair of Educational Activities. Affective Computing, Affective Neuroscience, Cognitive Neuroscience, Brain-Computer Interface, Neuromarketing, Neuroeconomics, Medical Image Processing, Machine Learning, and Artificial Intelligence are his primary interests. He has also guided 14 postgraduate students, 9 Ph.D., and 5 M.Sc.
He is currently an Editorial Board member for PLOS ONE (Q2), Human Centric Information Sciences (Q1), the Journal of Medical Imaging and Health Informatics (Q4), and the International Journal of Cognitive Informatics. He is serving as an editor in several peer-reviewed journals such as PlosOne, HCIS, JMIHI
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.
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.
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.
Gui-Bin Bian
Gui-Bin Bian is a Professor of Robotics, Institute of Automation, Chinese Academy of Sciences, Beijing, China.