Keynote Speakers
Renowned experts in nuclear and renewable energy sharing their insights
Prof. Dr. Madina Mansurova
Al-Farabi Kazakh National University, Kazakhstan
Short Bio:
Prof. Dr. Madina Mansurova is an experienced professor and researcher specializing in Artificial
Intelligence, Big Data, and high-performance computing. Over 30
years in academia, leading educational programs, international
projects, and scientific research. Strong expertise in teaching
operating systems, distributed systems, parallel computing, and AI in
Kazakh, Russian and English. Author of more than 150 scientific
papers, multiple textbooks and research monographs. Passionate
about developing innovative technologies, advancing education, and
guiding future IT specialists.
She is member of the Educational and
Methodological Association of the
Republican Educational and Methodological
Council of Higher and Postgraduate
Education of the Ministry of Higher
Education of the Republic of Kazakhstan in
the areas of Information Technology,
Information Security Systems
Title: From Energy Data Lakes to Sovereign AI: Building an AI-Ready Data Space for Nuclear and Renewable Energy Systems
Abstract: As energy systems become more digital, finding reliable information is not necessarily becoming easier. Power plants, renewable energy facilities, grid operators, and research organizations generate growing volumes of operational measurements, equipment records, weather data, technical standards, maintenance reports, and incident descriptions. Yet much of this information remains scattered across separate databases, document archives, and incompatible formats. The result is a paradox: more energy data are available, but engineers and researchers may still struggle to find, connect, and verify the information they need. An Energy Data Lake can help close this gap by bringing mixed energy datasets into a common and controlled environment. Structured measurements, operational records, and technical documents can be collected, cleaned, indexed, and linked with clear metadata and source information. This creates a practical basis for searching across different data types and for developing reliable AI services. A technical-document assistant built on this foundation can retrieve relevant information from equipment manuals, regulations, maintenance records, and incident reports. Instead of generating unsupported answers, it can provide responses together with references to the original documents, allowing specialists to review the evidence and judge whether the information is suitable for a particular engineering task. The central challenge is not simply to collect more data or use a larger language model. It is to build a trustworthy connection between energy data and AI-generated assistance. Such a system can support technical search, comparison of requirements, analysis of previous incidents, and access to operational knowledge while maintaining data sovereignty, traceability, and human responsibility.
Prof. Dr. Erdal Irmak
Gazi University, Türkiye
Short Bio:
Prof. Dr. Erdal Irmak, IEEE Senior Member, is a Professor of Electrical Engineering at Gazi University, Türkiye. His research interests include power system operation and control, renewable energy integration, smart grids, microgrids, energy storage systems, and the cybersecurity of critical infrastructures. He has authored more than 160 scientific publications, most of which are indexed in the Web of Science, and has led or participated in numerous national and international research and industrial projects. His recent work focuses on smart grid control, distributed energy resources, digital twin technologies, real-time energy management, and advanced power quality monitoring systems. Prof. Irmak serves as Editor or Associate Editor for several international journals and has held key organizational and technical roles in numerous IEEE-sponsored conferences. He currently serves as Head of the Smart Grids Graduate Program at Gazi University and teaches undergraduate and graduate courses in Electric Power Systems, Smart Grids, and Electrical Energy Distribution.
Title: Enabling the Renewable Energy Transition through Smart and Flexible Power Grids
Abstract: The increasing penetration of renewable energy resources is fundamentally transforming the operation and planning of electric power systems. While renewable generation plays a key role in the transition towards sustainable energy, its variable and distributed nature introduces significant challenges for grid stability, flexibility, reliability, and energy management. This keynote discusses the evolving role of smart and flexible power grids in addressing these challenges and enabling higher levels of renewable energy integration. Particular emphasis is placed on energy storage, advanced monitoring and control, and artificial intelligence as key enablers for improving grid flexibility and managing renewable generation variability. The presentation also highlights major integration challenges and emerging technological directions shaping the transition towards more sustainable, resilient, and intelligent power systems.