Call For

ICARC 2025 is now calling for full paper submission. Prospective authors are invited to
submit their full papers with maximum 06 pages.


We encourage the submission of high-quality papers reporting original work in both theoretical and experimental research in computing. The following tracks are hereby solicited.

Artificial Intelligence and Machine Learning:

Machine Learning, Deep Learning & AI, Fuzzy Logic and Fuzzy Systems, Hybrid Intelligent Systems, Information Retrieval, Robotics, Soft Computing and Applications, Probabilistic Reasoning, Evolutionary Computing, Hybrid Intelligent Systems, Software Agents, Soft Computing Theory and Applications, Web Intelligence Applications & Search, Advances in GenAI and XAI.
Text Analytics and Natural Language Processing:

Topic Recognition and Topic Tracking, Subject Indexing, Event and Anomaly Detection - Sentiment Analysis, Opinion, Personality and Emotion Detection in Social Media, Author Identification and Plagiarism Detection, Document Summarization and Identification, Similarity Analysis, Clustering, Hierarchic Clustering, Methods for Classification and Categorisation, Visualisation of NLP and IR Results, Ontologies, Knowledge Representation, Semantic Web Technologies, Ontology Generation and Query Expansion.
Computer Networks and Internet of Things:

Network Protocols and Architectures, Wireless Sensor Networks, Edge and Fog Computing, Security and Privacy, Network Virtualization and Software-Defined Networking, Blockchain IoT, IoT Healthcare, IoT Analytics, IoT and Cybersecurity, IoT Waste Management, IoT Artificial Intelligence, Smart Farming IoT, Smart Agriculture, Smart Cities, Smart Campus and Smart Villages, etc.
Knowledge Management and Software Engineering :

Information Systems Management, Information Systems and Technology, Knowledge Acquisition and Management, Information Systems Security, Knowledge Base Systems, Business Intelligence and CRM, KM Strategies and Implementations, Knowledge Management Projects, Tools and Technology for Knowledge Management, Software Engineering Methodologies, SOA and Service-Oriented Systems, AI and Software Engineering, Testing and Analysis, Empirical Software Engineering, Software Evolution, Formal Methods Applied to Software Engineering, Social Aspects of Software Engineering, Requirements Modeling and Design, Dependability.
Generative AI Enhanced Teaching and Learning :

Novel Pedagogical Perspectives and Theories on the Use of GenAI in Education, Using GenAI Tools to Support the Development of AI Literacy, Design and Development of GenAI-Based Educational Interventions, Supporting Collaborative Learning Processes, i.e., Collective Sense-Making, Creativity, Regulation/Socio-Metacognition, Societal and Ethical Considerations of the Use of GenAI in Education, GenAI Support for Non-Cognitive/Social-Emotional Skill Development (e.g., GenAI-Supported Tools and Curricula, Future Directions for Research on GenAI and Education)
Digital Transformation and Industry 5.0:

AI and Digital Transformation for Collaborative Systems, Distributed Cognition in Collaborative Systems, Collaborative, Resilient, and Sustainable Business Models and Production Systems, Collaborative Business Ecosystems, Cyber-Physical Systems and Their Applications in CNs, Value Creation and Impact of Collaborative Networks, Smart collaborative logistics and transportation Networks, Human-Machine Collaboration, Hybridization of Collaboration – Organizations, People, Machines, Systems, Agility, Resilience, and Sustainability of Networked Organizations, Human-Centric and Resilient Collaborative Systems, Industry 5.0, Agriculture 5.0, Healthcare 5.0, and Society 5.0, Ethics, Security, and Trust, Collaborative Digital Innovation Hubs, Applications and Case Studies in Multiple Fields, Collaborative Manufacturing and Factories of the Future, e-Health and Care, Food, Agribusiness, Agriculture 4.0, Crisis and Disaster Management, Digital supply chains, Collaborative e-Government, Mobility Networks, Urban Logistics and Smart Cities, Collaborative Energy Systems.
Digital Transformation in Healthcare :

AI for Medical Imaging -
Adaptation, Customization and Applications of Large Computer Vision Model (Such as the Segment Anything Model) for Medical Image Analysis, Small AI Models for Medical Image Analysis, Semi/Self Supervised Learning for Medical Image Analysis, Generative AI Models for Medical Image Analysis - Interpretability and Explainability of Medical Imaging AI Models, Any Other AI Techniques for Medical Imaging

AI for Medical Text-
Adaptation, Customization and Applications of Generative Large Language Models (Such as GPT-4, Palm, and Claude) for Digital Health Applications, Information Retrieval from Healthcare Text, Semantic Understanding of Healthcare Text, Dialogue and Interactive Systems for Healthcare Applications, Interpretability and Explainability of NLP Models, Any Other Novel NLP Models

AI for Personalized Treatment-
Reinforcement Learning Models for Treatment Recommendation, Recommendation Systems for Personalized Treatment, Transfer Learning to Adopt Knowledge to New Circumstances, Medical Digital Twin (Phenotyping) for Treatment Optimization, Ethical, Reliable and Fair Use of AI for Digital Health

Ethical Challenges and Issues for AI in Healthcare-
Use of AI to Ensure Fairness - Reliability of AI Models, Privacy Preserving in AI Models

Computing research papers which are not categorized under the above tracks are welcomed here.

All papers submitted to this conference will go through a double-blind peer review process handled by the Technical Program Committee. Acceptance will be based on the originality, significance, technical soundness, presentation, and references of the paper. The Technical Program Committee makes the final decision on the acceptance or rejection of a paper. IEEE Approval is pending for Accepted Papers will be submitted for inclusion into IEEE Xplore subject to meeting IEEE Xplore’s scope and quality requirements.