Dr. Santi P. Maity is a Professor (HAG) in Dept. of Information Technology in IIEST Shibpur. He served as the Head of various academic units of the Institute, namely Dept. of Information Technology, Purabi Das School of Information Technology (PDSIT), School of VLSI (SVLSI) and School of Mechatronics and Robotics (SMR) and School of Advanced Materials, Green Energy and Sensor Systems (SAMGESS). He received his B.E. degree in Electronics and Communication Engineering from National Institute of Technology Durgapur and M.Tech. in Microwaves from the University of Burdwan, India in 1993 and 1997, respectively. He received his Ph.D. degree in Engineering from IIEST Shibpur in 2008 and did Post-Doctoral work from January 2009 to July 2009 and February 2011 to July 2011 at the Laboratoire des Signaux et Systems (CNRS–Supelec–Universite Paris-Sud 11) in France. His research interests include Cognitive Radio Networks, Image Watermarking and Secret Sharing, Compressed Sensing on Medical Images and Disease Diagnosis using ML and DL techniques. His current research areas include the use of Reinforcement Learning (RL) on Spectrum Prediction, Reconfigurable Intelligent Surfaces (RIS) in IoT enabled D2D communications and Intelligent Transport System. He has published more than 350 research papers in International journals, International and National conference proceedings, and book chapters. He has guided 22 Ph. D scholars so far and examined more than 75 Ph. D theses of various institutes that include foreign institutes, State Universities, Central Universities, NITs, IITs and IIITs. He has delivered so far more than 80 invited, keynotes and tutorial talks in International and National conferences, seminars, workshops, symposiums and FDP program.
Abstract: Emergence of 5G and beyond (B5G) promise development of several applications specific Internet-of-Things (IoT) services involving various trustworthy intelligent and automated operations. However, IoT devices often need to work with limited storage, computation and power along with challenges on security threats and seamless-reliable wireless connectivity. Cognitive Communications involving intelligent spectrum sharing, reconfigurable intelligent surface (RIS), integrated Sensing and Communication (ISAC) and artificial intelligence driven computing need synergistic integration to address the above challenges. This lecture first introduces RIS and ISAC, then scope, challenges and opportunities in RIS-aided ISAC with artificial intelligence on some applications that include Gas monitoring, industrial automation, and healthcare support.
Prof. Ala’ Khalifeh currently works as a Professor of Computer Engineering at the School of Computing at the German Jordanian University (GJU). Prof. Khalifeh received the prestigious Fulbright Scholarship in 2005, which enabled him to pursue his doctoral degree from the University of California-Irvine in the United States of America. In September 2021, Prof. Khalifeh became a Fellow of the Innovation Leaders Fellowship (LIF) Program run by the Royal Academy of Engineering - UK. Prof. Khalifeh's research focuses on emerging technologies including the Internet of Things, artificial intelligence, datal analytics, cloud computing and wireless sensor networks. He has published several research papers in international conferences and indexed journals. Recognizing Prof. Khalifeh’s research impact, he recently was recognized by Stanford-Elsevier Ranking of Top 2% Top-cited Researchers Includes in 2023 and 2024.
Abstract: This talk explores the convergence of Artificial Intelligence, the Internet of Things, and Edge Computing to transform connected devices into intelligent systems. It highlights how AI can enable IoT devices to process data locally, make real-time decisions, and operate with greater autonomy. Key opportunities and challenges related to latency, energy efficiency, privacy, security, and resource constraints will be discussed. The talk will showcase practical applications and emerging trends such as TinyML, intelligent edge devices, and edge AI.
Prof. Dr. Chavis Srichan is a faculty member in the Department of Computer Engineering, Faculty of Engineering, Khon Kaen University (KKU), Thailand. He received his B.Eng. with First Class Honors from KKU, his M.Sc. from Hamburg University of Technology under the DAAD-Siemens program, and his D.Eng. from the Asian Institute of Technology. He also gained industrial experience at Siemens AG. His research focuses on biomedical sensing and data-driven intelligence, including Raman and SERS biosensors, noninvasive near-infrared glucose sensing, AI-enhanced nanobiosensors for kidney injury biomarkers, machine learning for early disease diagnosis, biophotonics, telemedicine, wireless communication, and quantum computing and cryptography. He has led and contributed to international collaborative projects, including NIH-US and ASEAN-IVO projects, and regularly serves as a reviewer, invited speaker, and session chair for academic conferences and journals.
Abstract: Intelligent ecosystems depend on data that is both accurate and trustworthy. This talk follows the path from raw signals to clinical decisions, and then asks how those decisions can be kept secure in a quantum era.The first part covers AI-powered optical sensing. It looks at Raman and SERS sensors, noninvasive near-infrared glucose sensing with lightweight shallow dense neural networks suited to portable, low-power devices, and AI-enhanced nanobiosensors for the kidney injury biomarker NGAL. It also covers functional near-infrared spectroscopy (fNIRS), where deep learning turns oxy- and deoxy-hemoglobin signals into estimates of brain activity and mental state. These support early detection and continuous monitoring of cancer, diabetes, kidney disease, and brain function.The second part covers quantum computing and cryptography. Health and neural data are sensitive and long-lived, so they need protection that will outlast today's public-key schemes. The talk presents recent work on:
• Hybrid QKD–ML-KEM key establishment
• Chaos-based post-quantum cryptographic constructions
• Quantum and post-quantum blockchain and forensic ledgers for tamper-evident records
• Quantum error correction and type-safe quantum programming
Across both parts, the talk discusses reproducibility, calibration, validation, interpretability (including motion artifacts and subject variability in wearable fNIRS), data security, and deployment in community healthcare. It closes with directions toward portable, noninvasive, quantum-secure intelligent health systems that suit national-scale ecosystems such as India's.
Dr. Iacovos Ioannou is an Assistant Professor of Computer Science at Neapolis University Pafos, Cyprus and an IEEE Senior Member. He is also a Senior Researcher at the CYENS Centre of Excellence, a Researcher at GÉANT Europe and a Scientific Collaborator of the Networks Research Laboratory (NETRL) at the University of Cyprus. He continues to teach part-time at Philips University. He received his Ph.D. in Computer Science from the University of Cyprus in 2021, holds an M.Sc. from the Open University of Cyprus awarded in 2016 and obtained his B.Sc. in Computer Science from the University of Cyprus in 2005. His research focuses on distributed artificial intelligence and machine learning for 5G/6G wireless networks, with particular interests in network optimisation and control, federated learning, IoT security and intrusion detection. His work also covers device-to-device communication, reconfigurable intelligent surfaces, localisation, edge and fog computing and the management of smart grids and microgrids.He is a co-author of Distributed Artificial Intelligence for 5G/6G Communications: Frameworks with Machine Learning, published by CRC Press in 2024. His research has appeared in journals including IEEE Internet of Things Journal, IEEE Open Journal of the Communications Society, IEEE Systems Journal, Computer Networks and Computer Communications. His project experience includes ADROIT6G, METACITIES and GÉANT GN5-2. He serves as an Associate Editor for IEEE Networking Letters and the International Journal of Antennas and Propagation. He has held technical programme and workshop chair roles at international conferences and has delivered keynote and invited talks. His industry experience includes software development at PrimeTel and IT administration and programming at the Cyprus Stock Exchange. He has taught undergraduate and postgraduate courses at several universities in Cyprus and has supervised B.Sc. and M.Sc. theses at the University of Cyprus.
Abstract: Wireless networks and power systems are converging on the same problem: both are becoming too large, too dynamic and too distributed to run from a central controller. 5G/6G must deliver ultra-high data rates, sub-millisecond latency, mass connectivity and cell-free architectures, while modern grids must absorb high shares of renewables, electric vehicles and smart loads in fragmented nano-grids. Although AI and machine learning have succeeded across many domains, their adoption in network and grid control remains slow.
This keynote presents a unified Distributed AI (DAI) framework built on Belief-Desire-Intention extended (BDIx) agents that act autonomously at the edge and collaborate to manage both domains. In communications, BDIx agents enable self-organising 5G/6G Device-to-Device networks, selecting plans and intentions for connectivity, energy efficiency, scalability and reliability without centralised orchestration. In energy, the same agent model provides distributed control of nano-grids, where we compare linear programming, PSO, genetic and ant-colony approaches and show that PSO reaches 98–99% of the optimal power efficiency while remaining scalable to large deployments. The talk covers the framework's architecture, its plan library and fuzzy-logic/ANFIS priority mechanisms, evaluation results in both domains, and its realisation in the EU ADROIT6G project and the nano-grid framework. It closes with open directions: game-theoretic multi-agent behaviour in non-cooperative settings, integration of D2D caching, functional metasurfaces and blockchain, and extension to autonomous vehicles, smart cities and industrial automation.
Filippo Sanfilippo holds a PhD in Engineering Cybernetics from the Norwegian University of Science and Technology (NTNU), Norway, with a focus on intelligent control approaches for robotic manipulators. His research focuses on human-robot teaming, artificial intelligence, and control theory. He is currently appointed as a Professor at the Faculty of Engineering and Science, University of Agder (UiA), Grimstad, Norway. He is also an adjunct Professor at the Faculty of Informatics, Kaunas University of Technology, Kaunas, Lithuania. He carries a vast experience in participating in European research programs and various national projects from the Research Council of Norway (RCN). He is an IEEE Senior Member. He is the former Chair of the IEEE Norway Section. He is the Chair of the IEEE Robotics and Automation, Control Systems and Intelligent Transportation Systems Joint Chapter. He is the Chair of the Norway Section Life Members Affinity Group. He is currently a member of the IEEE Region 8 Chapter Coordination Committee, of the Conference Coordination Committee, of the IEEE Public Visibility Committee, of the IEEE R8 Awards and Recognitions Committee, and of the Professional and Educational Activities Committee. He is also the former Treasurer of the Norsk Forening for Kunstig Intelligens (NAIS), the Norwegian Association for Artificial Intelligence. He has authored and co-authored several technical papers in various journals and conferences. He is a reviewer for several international conferences and journals.
Abstract: Human-robot interaction (HRI) is the study of how humans and robots interact, as well as how to develop robots that can adapt to human behavior. Human-robot cooperation (HRC) expands on this by creating new approaches and technologies that allow robots to collaborate with people in shared environments. The field of human-robot teaming (HRT) goes one step further, by studying how to create teams of humans and robots that can work together effectively and efficiently to achieve common goals. In this talk, an overview of the possible real-life applications for HRT will be presented.
Dr. Ola Buraik is an academic researcher, business strategist, and digital transformation specialist with expertise in Artificial Intelligence in Accounting, Financial Technology, intelligent financial systems, and corporate governance.She holds a Ph.D. in Accounting, with research focusing on artificial intelligence, internal control risks, and cloud governance in the banking sector.Her professional experience spans financial management, strategic planning, business development, and AI-driven organizational transformation.As Founder and CEO of Open Smart Strategic Solutions (OSSS), she leads initiatives integrating emerging technologies into business operations, financial management, and higher education.She is also actively involved in university transformation projects, developing AI-integrated academic programs, modern curricula, and institutional innovation initiatives, including projects supporting the modernization of higher education in Syria.Her work bridges academic research, industry practice, and emerging technologies to advance intelligent, sustainable, and data-driven organizations.
Abstract: Artificial Intelligence is transforming financial management from traditional transaction processing into intelligent, autonomous, and data-driven decision-making. The emergence of Agentic AI represents a significant shift toward systems capable of analyzing financial information, supporting complex decisions, and continuously monitoring organizational performance.This keynote explores the evolution of AI-powered financial ecosystems through three interconnected levels: intelligent accounting automation, continuous financial reporting and predictive analytics, and AI-assisted strategic financial management.The talk highlights how Agentic AI, machine learning, and intelligent ERP systems can enhance financial forecasting, risk assessment, corporate governance, and executive decision-making.It also addresses the importance of human oversight, transparency, and responsible AI adoption in financial environments.By connecting academic research with practical digital transformation initiatives, this keynote presents a forward-looking framework for the evolution of intelligent financial management and the emerging role of the AI-powered CFO.
