Raffaele Carli received his Laurea degree in Electronic Engineering with honours in 2002 and his PhD in Electrical and Information Engineering in 2016, both from Politecnico di Bari, Italy. From 2003 to 2004, he was a Reserve Officer with Italian Navy. From 2004 to 2012, he worked as System and Control Engineer and Technical Manager for a multinational company in the space and defense sector.
Currently, Dr. Carli is an Associate Professor in Systems and Control Engineering at Politecnico di Bari, where he is the technical lead for the Decision and Control Laboratory (coordinated by prof. Mariagrazia Dotoli) within the Department of Electric and Information Engineering (http://dclab.poliba.it/). He has held national qualifications as a Full Professor since 2023. Since 2022, he has served as Vice-Coordinator of the National PhD program in Autonomous Systems (http://dausy.poliba.it/phd/).
Dr. Carli serves on the editorial board of IEEE (Institute of Electrical and Electronics Engineers) journals as an Associate Editor for IEEE Transactions on Automation Science and Engineering (awarded 2023 and 2024 Best Associate Editor) and IEEE Transactions on Systems, Man, and Cybernetics. He is also an active member of the conference editorial boards of various events sponsored by IFAC (International Federation of Automatic Control) and IEEE, including those sponsored by the IEEE Control Systems Society (CSS), IEEE Robotics and Automation Society (RAS), and IEEE Systems, Man, and Cybernetics Society (SMCS). His organizational roles include positions on the committees of several IEEE conferences, such as Young Career Chair of the 2017 IEEE International Conference on Automation Science and Engineering, Publication Co-chair of the 2015 IEEE International Conference on Automation Science and Engineering, Tutorial Co-chair of the 2023 IEEE International Conference on Systems, Man and Cybernetics, Finance Chair and Special Session Chair of the 2024 IEEE International Conference on Automation Science and Engineering. He also serves as General Chair of the upcoming IFAC Workshop on Smart Energy Systems for Efficient and Sustainable Smart Grids and Smart Cities (SENSYS 2025) and the Publicity Chair of the 2026 IEEE International Conference on Industrial Electronics and Applications.
An IEEE Senior Member since 2022, Dr. Carli currently serves as the Mentorship Subcommittee Chair of the Membership and Student Activities Committee within the IEEE SMCS for the 2023-2024 and 2025-2026 terms. Additionally, he currently serves as the Secretary of the IEEE Italy Section Chapter CS23 of the CSS for the 2025-2026 term.
Dr. Carli has authored over 120 printed international publications (Google Scholar profile: https://scholar.google.it/citations?user=OvXT8Y0AAAAJ&hl=en). His research focuses on developing decision and control techniques for modeling, optimizing, managing, and controlling complex, large-scale systems, particularly in smart frameworks such as industry and energy. He received the 2024 IEEE Italy Section SMCS Chapter Award for Excellence in Early Career Research.
For additional information, visit: http://dclab.poliba.it/people/raffaele-carli/
Title: Control Techniques for the Energy–Agriculture Nexus: The Case of Vertical Farms
Abstract: The growing global demand for sustainable food production and the scarcity of arable land are accelerating the adoption of controlled-environment agriculture, with vertical farms (VFs) emerging as an innovative solution. However, their high energy consumption poses significant challenges to both sustainability and economic feasibility. This talk presents advanced decision and control techniques designed to optimize crop growth conditions while reducing energy costs and enabling participation in demand response programs. In particular, it introduces a novel control framework integrating vertical farm operation with dynamic energy market participation through centralized and decentralized receding horizon control strategies. Experimental and simulation results highlight the benefits in terms of cost reduction, scalability, and environmental sustainability, demonstrating the potential of control-based optimization to enable efficient and resilient agricultural systems.
Eng. Dr. Dennis N. Mwighusa is a distinguished AI expert, academic, researcher, and consulting engineer with over 15 years of experience in Artificial Intelligence, Machine Learning, Deep Learning, Computer Vision, Cognitive Computing, and other emerging technologies. He currently serves as the Executive Director of the Africa Research Institute For AI (ARIFA), where he leads research, policy development, and capacity-building initiatives aimed at advancing responsible and impactful AI across Africa.
Dr. Mwighusa holds a PhD in Image Processing, an MEng in Signal and Information Processing, a BEng in Computer Science and Engineering, and a Higher National Diploma in AI and Cognitive Computing. His work focuses on applying AI and data-driven technologies to address complex societal and development challenges while promoting innovation, digital transformation, and sustainable technological growth.
He collaborates with governments, international organizations, development partners, and research institutions in shaping national, regional, and global AI strategies and governance frameworks. In addition to his research and advisory roles, Dr. Mwighusa serves as an adjunct professor at both local and international universities, contributing to teaching, curriculum development, and mentorship in Artificial Intelligence and related fields.
A prolific researcher and international speaker, he has published widely in reputable scientific journals and has supervised over 15 postgraduate students. His contributions have earned him several recognitions, including IEEE Distinguished Young Professional Innovator 2025 and ICT Expert of the Year (2021 & 2022).
Title: From Readiness to Real Impact: Governing and Scaling Artificial Intelligence for Sustainable Development in Emerging Economies
Abstract:
Artificial Intelligence is rapidly transforming industries, governments, and societies worldwide. However, for many emerging economies, the challenge extends beyond simply adopting AI technologies to building the institutional capacity, governance structures, and data ecosystems required for AI to generate meaningful societal impact. This keynote will explore how countries can transition from early experimentation with AI toward responsible, scalable, and development-oriented deployment.
Drawing on practical experiences from AI readiness assessments, policy advisory engagements, and applied research across the Global South, the keynote will highlight how governments, research institutions, and industry can collaborate to build effective AI ecosystems that support economic growth, financial inclusion, digital public infrastructure, and evidence-based policymaking. Particular attention will be given to lessons from emerging economies on AI governance frameworks, regulatory preparedness, data infrastructure, and talent development.
The presentation will also examine the growing role of AI in strengthening financial intelligence systems, optimizing energy infrastructure, and enhancing digital government services. These applications demonstrate how intelligent technologies can address complex challenges while improving efficiency, transparency, and accessibility.
By integrating policy insights, real-world case studies, and forward-looking perspectives, the keynote will illustrate how responsible AI development can become a powerful driver of inclusive innovation and sustainable development in emerging economies navigating rapid digital transformation.
Dr. Tulsi Pawan Fowdur received his BEng (Hons) degree in Electronic and Communication Engineering with first class honours from the University of Mauritius in 2004. He was also the recipient of a Gold medal for having produced the best degree project at the Faculty of Engineering in 2004. In 2005 he obtained a full-time PhD scholarship from the Tertiary Education Commission of Mauritius and was awarded his PhD degree in Electrical and Electronic Engineering in 2010 by the University of Mauritius. He joined the University of Mauritius as an academic in June 2009 and is presently an Associate Professor at the Department of Electrical and Electronic Engineering of the University of Mauritius. He has served as Faculty Research Advisor from April 2022 to July 2024 at the Faculty of Engineering and Vice Chair of the IEEE Mauritius Section from January 2022 to December 2025. He is also a Registered Chartered Engineer of the Engineering Council of the UK, Fellow of the Institute of Telecommunications Professionals (UK), Senior Member of the IEEE and Editorial Board Member of Scientific Reports. His research interests include Mobile Communications, Artificial Intelligence, Networking, Cybersecurity, Telecommunications Applications Development, Industry 4.0, Energy Efficient Communications and Internet of Things. He has over 150 publications in these areas including nine books and is actively involved in, PhD supervision, editorial tasks and the organization of international conferences.
Title: Generative and Agentic AI Automation for Network QoS and Security Analytics
Abstract:
Network Quality of Service (QoS) and cybersecurity remain two of the most critical challenges facing both Internet users and service providers, particularly in the context of increasing demands for ultra-reliable low-latency communications and the growing sophistication of AI-enabled cyber threats. Recent advances in Generative and Agentic are transforming network management by enabling intelligent automation, predictive analytics, self-optimization, and autonomous decision-making. These capabilities are expected to play a central role in future AI-native communication systems, including 6G radio access networks that can autonomously adapt, optimize, and self-heal in response to changing network conditions.
While much of the current focus is on operator-side deployment of AI technologies, similar benefits can also be delivered directly to end users. Since web browsers serve as the primary interface through which users access network services, they provide an ideal platform for integrating AI-powered QoS and security analytics. This keynote presents a browser-extension-based framework that combines network monitoring, Generative AI, Agentic AI, and workflow automation to provide intelligent analysis of network performance and security. The proposed system collects QoS and security-related parameters through a browser extension, forwards them to an AI automation platform via webhooks, performs preprocessing and orchestration, and leverages AI models for real-time analysis and decision support. The resulting insights are then returned directly to the user's browser in an intuitive and actionable format. The keynote will discuss the design, implementation, and deployment of such AI-enabled monitoring systems, highlighting how low-code automation platforms, browser technologies, and modern AI models can be combined to deliver advanced network analytics in a user-friendly manner. The presentation will also explore the benefits of integrating Generative and Agentic AI within AI-native communication systems to enhance network resilience, security, and quality of experience.