Special Session 1: Internet of Things and Artificial Intelligence (CFP Download)

Session Organizer: Prof. Rajeev Kanth, Savonia University of Applied Sciences and University of Turku, Finland

Subtopics: Industrial Internet of Things, IoT and Digital Health Ecosystem, IoT and Edge computing, ML and DL in IoT ecosystem, Any other topics related to the main session theme.

Research Scope: IoT related research that includes IoT design, development, framework building, architectural research where Artificial intelligence can be utilized to perform insightful decision in any application domain of the development.

Submission Method: Submit your Full Paper (no less than 8 pages) or your paper abstract-without publication (200-400 words) via Online Submission System, then choose Special Session 1 (Internet of Things and Artificial Intelligence)
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Prof. Rajeev Kanth
Savonia University of Applied Sciences and University of Turku, Finland

Biography: Prof.(h.c.) Rajeev Kanth received a Doctor of Science (D.Sc.) in Information and Communication Technology from the University of Turku, Finland, in 2013. He has been working as a Principal Lecturer (Yliopettaja- in Finnish) at the Savonia University of Applied Sciences, Finland, where he focuses on teaching and research on the Internet of Things (IoT). He has been an Adjunct Professor at the Department of Computing, University of Turku, Finland, and an honorary Professor at Hebei University of Environmental Engineering, China. He is currently a senior member of the IEEE. Previously, he worked at the Indian Space Research Organization (ISRO), Ahmedabad, India, and the Royal Institute of Technology (KTH), Stockholm, Sweden, where he was a researcher and a senior research scientist, respectively. He has over 25 years of experience working in academic and research institutions. His current research interests include the Internet of Things, big-data analytics, artificial intelligence, and wireless cloud and edge computing. He has published more than 100 scientific articles in peer-reviewed conference proceedings and refereed computer science and communication technology journals. Some of the recent and ongoing research and development projects are UCNDRONE (funded by the Finnish Ministry of Education), VLEFACT (EU Erasmus Plus-funded project), and AIQUSEC (Business Finland).

Special Session 2: Trustworthy AI: Evaluation Frameworks, Governance, and Real-World Applications(CFP Download)

Session Organizer: Asst. Prof. Ahlam Shakeel Ahmed Ansari, M. H. Saboo Siddik College of Engineering, India

Description: As AI systems become embedded in critical decision-making pipelines, evaluating their trustworthiness demands a rigorous, multidimensional lens that goes far beyond conventional performance metrics. This special session invites original contributions exploring composite trust scoring, explainability, fairness, robustness, and regulatory alignment across AI paradigms. We welcome papers that bridge theoretical frameworks with applied deployments — particularly in healthcare, finance, and autonomous systems — contributing to the global conversation on accountable and auditable AI.

The topics of interest include, but are not limited to:

1. Beyond Accuracy: Multi-Dimensional Trustworthiness Evaluation of AI Systems
2. Governing the Black Box: Frameworks for Explainability and Accountability in AI
3. Trustworthy AI in High-Stakes Domains: Healthcare, Finance, and Autonomous Systems
4. Composite Trust Scoring: MCDM Approaches for Quantifying AI Reliability
5. Regulatory-Aligned AI: Mapping Systems to NIST AI RMF, EU AI Act, and ISO/IEC 42001
6. Federated Learning and Privacy-Preserving Architectures as Trust Enablers

Submission Method: Submit your Full Paper (no less than 8 pages) or your paper abstract-without publication (200-400 words) via Online Submission System, then choose Special Session 2 (Trustworthy AI: Evaluation Frameworks, Governance, and Real-World Applications)
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Asst. Prof. Ahlam Shakeel Ahmed Ansari
M. H. Saboo Siddik College of Engineering, India

Biography: Ahlam Shakeel Ahmed Ansari is an Assistant Professor of Computer Engineering at M. H. Saboo Siddik College of Engineering, Mumbai, with over 16 years of teaching and research experience. She is is researching — "A Unified Framework for Evaluating Trustworthiness of AI Systems (UFE-TAIS)" — develops a paradigm-aware composite trustworthiness scoring pipeline anchored to the NIST AI RMF, EU AI Act, and ISO/IEC 42001. Her research spans trustworthy AI evaluation, federated learning, privacy-preserving AI, AI governance, and MCDM (BWM-TOPSIS) methodologies, with applications in healthcare and cybersecurity. She holds 20+ publications and credentials, including Google Certified Educator (Levels 1, 2 & Gemini), Mendeley Advisor, SciSpace Ambassador, and MIT JWEL membership.

Special Session 3: AI in Smart Education and Learning Technologies — Reshaping Tools, Teaching, and Learnings(CFP Download)

Session Organizer: Mr. Miguel J. Puig, National University – Mall of Asia, Philippines

Subtopics: Machine Learning and Predictive Analytics in Smart Learning Environments, AI-Assisted Assessment and Automated Feedback Systems, Ethical AI Frameworks and Bias Mitigation in Educational Technology, Pattern Recognition in Special Education and Learning Behavior Analysis, Personalized and Adaptive Learning Algorithms, Human-in-the-Loop AI for Innovative Pedagogical Methods, Any other topics related to the main session theme.

Research Scope: Smart education and educational technology research that includes machine learning algorithm design, predictive data analytics, adaptive system frameworks, and ethical AI integration where artificial intelligence and data-driven methods can be utilized to transform instructional tools, optimize teaching strategies, and enhance personalized learning outcomes across diverse learning environments.
 
Submission Method: Submit your Full Paper (no less than 8 pages) or your paper abstract-without publication (200-400 words) via Online Submission System, then choose Special Session 3 (AI in Smart Education and Learning Technologies — Reshaping Tools, Teaching, and Learnings)
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Mr. Miguel J. Puig
National University – Mall of Asia, Philippines

Biography: Miguel J. Puig is currently a Professor at the School of Information Technology, National University (NU) – Mall of Asia, Philippines.
Mr. Puig is an active member of the Philippine Society of Information Technology Educators (PSITE) and serves as a technical peer reviewer for international academic conferences, His primary research specializations center on Data Science, Machine Learning, and Algorithmic Design, with a dedicated focus on AI in smart education, learning behavior pattern analysis (including special education for students with autism), ethical AI integration, and educational data analytics. In addition to his academic research, he brings extensive hands-on experience in software engineering, system architecture, and applied database systems.