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.

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I told my colleagues that PeerJ is a journal where they need to publish if they want their paper to be published quickly and with the strict peer review expected from a good journal.
Sohath Vanegas,
PeerJ Author
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Waqar Shahid Qureshi

Dr. Waqar Shahid Qureshi is an applied AI researcher and engineer with over 22 years of professional experience across academia, research, and industry. His interdisciplinary expertise lies in artificial intelligence, computer vision, robotics, and intelligent sensing systems, with a strong emphasis on real-world deployment in precision agriculture, consumer electronics, and civil infrastructure.

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Elizabeth D Mynatt

Executive Director of the Institute for People and Technology and Professor in the College of Computing at the Georgia Tech. Her research program, known as Everyday Computing, examines the human-computer interface implications of having computation continuously througout everyday life. She is a member of the SIGCHI Academy, a Sloan and Kavli research fellow, and serves on Microsoft Research's Technical Advisory Board. Mynatt is also the Vice-Chair of the Computing Community Consortium.

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Bálint Molnár

Dr. Bálint Molnár is an Associate Professor and Lecturer within the Department of Information Systems at Eötvös Loránd University, Budapest, Hungary.

His research interests include, but are not limited to, Formal, mathematical-based models for designing, modeling, and validating information systems; Application of data science methods to solve data, function, and process integration issues of enterprise management and health information systems. Enterprise, organizational, business, information systems architecture, and application of formal models.

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Mohammad Zavid Parvez

Mohammad Zavid Parvez is a scholar in computer science with over 16 years of academic and research experience spanning machine learning, biomedical signal processing, cybersecurity, and federated learning. He earned his PhD in Computer Science from Charles Sturt University, Australia, where his research focused on epileptic seizure detection and prediction using EEG signals, and has since held research positions at Charles Sturt University and the ISI Foundation (Italy). He has published extensively in leading journals, including IEEE Transactions on Biomedical Engineering, IEEE Transactions on Neural Systems and Rehabilitation Engineering, and Neurocomputing. He also serves as Topic Editor for Frontiers in Medicine. His current research interests include cyber threat intelligence, privacy-preserving medical data analysis, and AI-driven healthcare solutions.

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Alicia Fornes

Alicia Fornés is a Staff Scientist in the Document Analysis Group within the Computer Vision Center at the Universitat Autònoma de Barcelona.

Her research interests include document image analysis, graphics recognition, digital humanities, handwriting recognition, historical documents and optical music recognition.

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Hamid Mcheick

Dr. Hamid Mcheick is a full professor in Computer Science department at the University of Québec at Chicoutimi, Canada. He has more than 25 years of experience in both academic and industrial areas. He has done his Ph.D. in Software Engineering and Distributed System in the University of Montreal, Canada. He is working on designing of adaption distributed, smart and connected software applications; designing healthcare frameworks; and designing smart Internet of Things architecture. He has supervised many post-doctorate, PhD, master, and bachelor students. He has nine book chapters, more than 60 research papers in international journals, and more than 150 research papers in international/national conferences and workshop proceedings to his credit. Dr. Mcheick has given many keynote speeches and tutorials in his research area, particularly in Healthcare systems, Architecture Pervasive and Ubiquitous Computing, Distributed Middleware Architectures, Software Connectors, Service-Oriented Computing, Internet of Things (IoT), Smart Architectural Frameworks, Mobile Edge Computing, Fog Computing, and Cloud Computing. Dr. Mcheick has gotten many grants from governments, industrials and academics. He is a chief in editor, chair, co-chair, reviewer, member in many organizations (such as IEEE, ACM, Springer, MDPI, Elsevier, Inderscience) around the world.

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Gopikrishna Deshpande

Prof. Gopikrishna Deshpande is a Professor of Electrical and Computer Engineering at Auburn University. He obtained his Ph.D. in Medical Imaging from Georgia Institute of Technology and his M.S. in Electrical and Computer Engineering from the Indian Institute of Science.

Prof. Deshpande's research interests and expertise include neuroimaging, functional magnetic resonance imaging (fMRI), brain connectivity, signal/image processing and machine learning.

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Eui-Nam Huh

Dr. Eui-Nam Huh is a Professor within the Department of Computer Science and Engineering at Kyung Hee University, South Korea.

His expertise is focused on cloud computing and machine learning.

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Zheng Yuan

Dr. Zheng Yuan is a Lecturer in Artificial Intelligence (Natural Language Processing) at Kings College London.

Dr. Yuan holds a PhD and an MPhil from the University of Cambridge, and a BSc in Engineering from Queen Mary University of London and Beijing University of Posts and Telecommunications. Before joining King’s, Zheng was a Research Associate at the University of Cambridge, where she is still a Visiting Researcher.

Her research interests include, Educational NLP, Language acquisition, Multilingual NLP, Machine translation, Neural networks and deep learning, Transfer and multi-task learning, Unsupervised and semi-supervised learning, and Explainable machine learning.

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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.

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Ilkay Altintas

Ilkay Altintas is a research scientist at SDSC, UCSD since 2001. She has worked on different aspects of data science and scientific computing in leadership roles across a wide range of cross-disciplinary projects. She is a co-initiator of and an active contributor to the open-source Kepler Workflow System, and co-author of publications at the intersection of scientific workflows, provenance, distributed computing, bioinformatics, sensor systems, conceptual data querying, and software modeling.

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Mario Silic

Mario Silic brings over 30 years of international professional experience in senior management and consultancy roles. He has held leadership positions at global corporations including Epson, HP, Alcatel, Western Union, and Renault, and has advised prestigious organizations such as the City of Barcelona, AUDI, the City of Munich, and Ericsson.

He earned his PhD from the University of St. Gallen, Switzerland, where his research in cybersecurity was recognized and supported through multiple grants, including the GFF Project (2015), GFF Postdoctoral Fellowship (2016), and the Swiss National Science Foundation Postdoctoral Project Grant (2017). His scholarly work focuses on artificial intelligence, cybersecurity, information security, open-source software, and mobile technologies, with a notable contribution on mitigating insider computer abuse in cybersecurity contexts.

As an educator, Mario is passionate about bridging research and practice. He teaches a wide range of courses, including Cybersecurity, Applied AI and Machine Learning for Business, Data Analytics and Decision-Making, Programming, Project Management, Innovation Management, and Web Technologies. His teaching philosophy emphasizes practical application and preparing students to thrive in the fast-evolving digital economy.