The volume and complexity of data generated by various systems, sensors, and devices continue to rise at an unprecedented rate in today's data-driven world. This data flood presents opportunities and challenges, especially in large-scale distributed environments where traditional computing approaches frequently fail to keep up. Cognitive computing is an innovative and transformative field that combines the power of artificial intelligence (AI), machine learning, natural language processing, and advanced analytics to mimic human cognition and significantly improve computing systems' capabilities. Today, most applications use AI for faster and more intelligent responses. Distributed data has various sources and formats to process the single entity. Neural networks are intelligent machines trained using different concepts based on application. It is competent for distributed datasets and large-scale applications. Many natural language processing applications are now available as cloud services. These services rely on distributed computing to provide many users and applications with scalable and efficient NLP capabilities.

The special issue investigates the relationship between cognitive technologies and distributed computing systems. This situation represents a paradigm shift in processing, analysing, and deriving meaningful insights from massive datasets while making informed decisions in complex and dynamic situations. Distributed computing solutions have become critical as organisations deal with the ever-increasing demands of large-scale data processing. However, cognitive capabilities that enable autonomous learning, adaptability, and intelligent decision-making must be infused into them to realise the true potential of distributed systems. This special issue investigates the relationship between cognitive computing and distributed data processing, shedding light on how these technologies can help organisations address their most pressing challenges.

Recommended topics (but not limited to)

This special issue invites original research articles and review articles on the following topics of interest.

• Cognitive frameworks and architectures for distributed data processing.
• Natural language processing's role in improving communication and decision-making in distributed systems.
• Machine learning techniques for distributed data analytics and their integration with cognitive computing.
• The development and application of cognitive decision support systems.
• Security and trust considerations in cognitive distributed systems.
• Emerging technologies such as edge computing and quantum computing in conjunction with cognitive algorithms.
• Real-world applications and use cases, including healthcare diagnostics and intelligent cities.

Important dates

Submission deadline: 28 February, 2025

Authors notification: 31 May, 2025

Revision submission: 31 July, 2025

Submission guidelines

Original and unpublished works on any of the topics aforementioned or related are welcome. The SCPE journal has a rigorous peer-reviewing process and papers will be reviewed by at least two referees. All submitted papers must be formatted according to the journal's instructions, which can be found here.

During submission please select a Special Issue that you want to submit to and provide this information in the Comments for the Editor field.

Guest Editors

Dr. Rajkumar Rajavel, Associate Professor, Department of Computer Science and Engineering, CHRIST (Deemed to be University), Mysore Road, Bangalore, Karnataka-5670074, India, email: rajkumar.rajavel@christuniversity.in

Rajkumar Rajavel is an Associate Professor in the Department of Computer Science and Engineering, Christ University, Bangalore, India. Completed Ph.D. as Anna Centenary Research Fellow in the Department of Information Science and Technology, Anna University, India during the year 2016. He has obtained his M.Tech Graduate in the specialization of Information Technology during the year 2010. His research areas include Cloud Computing, Big Data Analytics, Artificial Intelligence, and Machine Learning Techniques. He has presented 6 research publications in the international conferences and published more than 12 papers in the reputed SCI Indexed journals.

Dr. Nebojša Bačanin-Džakula, Full Professor, Vice-Rector for Scientific Research, Univerzitet Singidunum/Singidunum University, Serbia, email: nbacanin@singidunum.ac.rs

Nebojsa Bacanin received his Ph.D. degree from Faculty of Mathematics, University of Belgrade in 2015 (study program Computer Science, average grade 10,00). He started University career in Serbia 15 years ago at Graduate School of Computer Science in Belgrade. He currently works as a Full Professor, Vice-rector for Scientific Research and as a Head of Applied Artificial Intelligence Department at Singidunum University, Belgrade, Serbia. He is involved in scientific research in the field of computer science and his specialty includes stochastic optimization algorithms, swarm intelligence, soft-computing and optimization and modeling, as well as artificial intelligence algorithms, swarm intelligence, machine learning, image processing and cloud and distributed computing. He has published more than 320 scientific papers (more than 130 papers indexed in Clarivate Analytics SCIE) in high quality journals and international conferences indexed in Clarivate Analytics JCR, Scopus, WoS, IEEExplore, and other scientific databases, as well as in Springer Lecture Notes in Computer Science and Procedia Computer Science book chapters. He has also published 4 books in domains of Cloud Computing, Web Programming and Advanced Java Spring Programming. He is a member of numerous editorial boards, scientific and advisory committees of international conferences and journals. He is a regular reviewer for international journals with high Clarivate Analytics and WoS impact. He actively participates in 1 national and 1 international projects from the domain of computer science. He has also been included in the prestigious Stanford University career list with 2% best world researchers in the field of Artificial Intelligence.

Dr. Durga Prasad Bavirisetti, Norwegian University of Science and Technology, Norway, email: durga.bavirisetti@ntnu.no

Dr. Durga Prasad Bavirisetti is a researcher at the Norwegian University of Science and Technology, Norway. He received a Ph.D. in Computer Vision from VIT, Vellore, India. He pursued his Postdoctoral research at Shanghai Jiao Tong University, China, and was a Visiting Researcher at the University of British Columbia, Okanagan, Canada. He worked as an Algorithm Expert at the Department of AI of Alibaba Research Lab, Alibaba Group of Companies, Shanghai. He also worked as a contract researcher at the Norwegian University of Science and Technology, Norway.

Dr. Mohamed Abouhawwash, Michigan State University, East Lansing,
MI, 48824, USA, email: abouhaww@msu.edu

Dr Mohamed Abouhawwash, received the BSc and MSc degrees in statistics and computer science from Mansoura University, Mansoura, Egypt, in 2005 and 2011, respectively. He finished his Ph.D. in Statistics and Computer Science, 2015, in a channel program between Michigan State University, USA, and Mansoura University, Egypt. He is at Computational Mathematics, Science, and Engineering (CMSE), Biomedical Engineering (BME) and Radiology, Institute for Quantitative Health Science & Engineering (IQ), Michigan State University, East Lansing, MI 48824, USA. He is an Associate Professor with the Department of Mathematics, Faculty of Science, Mansoura University, Egypt. In 2018, Dr. Abouhawwash is a Visiting Scholar with the Department of Mathematics and Statistics, Faculty of Science, Thompson Rivers University, Kamloops, BC, Canada. His current research interests include evolutionary algorithms, machine learning, image reconstruction, and mathematical optimization. Dr. Abouhawwash was a recipient of the best master’s and Ph.D. thesis awards from Mansoura University in 2012 and 2018, respectively.