Geert Deconinck is a full professor at KU Leuven , leading the Electrical Energy Systems and Applications (ELECTA) research group within the Department of Electrical Engineering (ESAT). He also serves as scientific leader of the EnergyVille research center's algorithms domain, focusing on smart electrical networks and thermal systems. M.Sc. and Ph.D. from KU Leuven Head of ELECTA since 2012 (10 professors, 8 postdocs, 70+ PhDs) Over 8 million EUR research budget in last 5 years 44 completed PhDs and 10 current advisees IEEE Transactions editorial board member His research spans smart grid architectures , distributed control , and cyber-physical security , with recent focus on EV-grid integration , renewable energy democratization , and multi-carrier energy systems . Current projects include: Smart Charging - E-Mobility meets Renewable Energy Early Detection and Defense Systems for Smart Grids Open-source P2P energy sharing platforms Microgrid control strategies for PV-battery systems Awarded IET Fellow and IEEE Senior Member status, his work combines machine learning with power systems engineering through both theoretical modeling and experimental validation . He has contributed over 575 publications with 9800+ Google Scholar citations.
Lars Nordström is a Professor at the Division of Electric Power and Energy Systems within KTH Royal Institute of Technology, Stockholm, Sweden. His work bridges control systems , communication networks , and power systems , with a focus on future architectures, functionality, and quality aspects of ICT for power grid operations. He has led initiatives such as the Swedish Centre of Electric Power Engineering and served as Thematic Leader for Smartgrids in KIC InnoEnergy. In 2014, he was a Visiting Professor at Washington State University. Education : Ph.D., MSc.EE Nordström's research explores the intersection of smart grids , machine learning , and cybersecurity for power systems. Key areas include: Wide-Area Monitoring and Control (WAMC) systems Decentralized control strategies for DC microgrids Impedance modeling using neural networks Data-driven methods for islanding detection ICT reliability and protocol design for grid operations His recent publications emphasize machine learning applications in power systems, including LSTM networks for EV charging management, graph attention networks for stability monitoring, and digital twin approaches for cyber-attack mitigation. These works span disciplines such as Smart Grids, Power Electronics, and Data Science. Scientific Recognitions : Senior Member, IEEE Senior Member, CIRED Senior Member, Cigre Past Chairman, Swedish IEC TC57 Mirror Committee Nordström actively teaches and examines graduate courses like Communication and Control in Electric Power Systems and Computer Applications and Machine Learning in Electric Power Systems . His work influences industry practices through collaborations on digital substations, energy market analysis, and resilience strategies.
Professor Gregor Verbic is a faculty member at the University of Sydney in the School of Electrical and Computer Engineering , where he serves as Director of the Centre for Future Energy Networks . Previously, he held an assistant professor position at the University of Ljubljana and was a NATO-NSERC Postdoctoral Fellow at the University of Waterloo. His career spans academic research, industry leadership as Head of Interenergo's Investment Department, and extensive collaboration with IEEE. PhD in Electrical Engineering (University of Ljubljana) Senior IEEE Member Research Interests focus on transforming power systems to zero-carbon grids through: Aggregation and control of distributed energy resources (DERs) Frequency control with wind generation and electric vehicles Stochastic optimization for multi-energy systems Smart home energy management with phase change materials Notable Contributions include: 2006 IEEE prize paper for voltage instability prediction 2010-2024: 15 recent publications on DER coordination, network tariffs, and low-inertia grid stability Teaching includes courses on: ELEC3203/ELEC9203: Electricity Networks ELEC5213: Engineering Optimisation ELEC5206: Sustainable Energy Systems Labs & Initiatives Centre for Future Energy Networks The Net Zero Institute
Jan Carmeliet is a Full Professor at the Department of Mechanical and Process Engineering at ETH Zürich , holding the Chair of Building Physics since 2008. He previously held academic positions at Katholieke Universiteit Leuven and Eindhoven University of Technology . His research focuses on multiscale modeling of porous and granular materials , urban heat-air-moisture flows , and energy-efficient urban systems . His work integrates advanced computational techniques (e.g., lattice Boltzmann methods , CFD , FEM ) with experimental approaches ( X-ray tomography , wind tunnel PIV ). He leads major projects such as the RePoDH and Urban Multiscale Energy Modelling initiatives, aiming to decarbonize urban energy systems and understand local heat islands. Current projects emphasize renewable-powered district heating networks and urban climate modeling . Key collaborations include institutions like Empa , University of Illinois , and Los Alamos National Laboratory . He has secured significant grants from the Swiss National Science Foundation (SNSF) and ETH Domain , focusing on urban energy resilience and material science. His leadership roles include directing the Energy Science Center ETH Zürich and coordinating the SCCER-efficiency program.
Dr. Andrzej Ożadowicz is a University Professor at the Department of Power Electronics and Automation of Energy Conversion Systems within the Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering at AGH University of Science and Technology in Kraków, Poland. His office is located in room 510, building C-1, with contact details including phone +48 12 617 50 11 and email ozadow@agh.edu.pl. He holds PhD, DSc, and Engineering degrees, reflecting his dual expertise in academic research and practical engineering applications. His research spans Power Electronics, Building Automation, Smart Grids, and IoT-driven energy systems. Key interests include energy efficiency optimization through digital twins and BIM, distributed energy resource integration , and AI-enhanced demand management . Notably, he pioneers applications of deep reinforcement learning in home energy systems and develops frameworks for Smart Readiness Indicator implementation. His work bridges theoretical innovation with practical case studies in building thermal modeling and dynamic façade systems. Recent publications (2021-2025) reveal three dominant trends: (1) Convergence of digital twin technology with building automation for real-time energy management; (2) Critical analysis of IoT security and interoperability in smart infrastructure; (3) Pedagogical innovations in engineering education through blended learning methodologies post-COVID-19. His scholarly output demonstrates consistent focus on energy transition challenges and smart grid evolution. Professor Ożadowicz actively contributes to the Discipline Council for Automation, Electronics, Electrical Engineering and Space Technologies at AGH. He is instrumental in the AutBudNet initiative —a network of certified laboratories for energy efficiency assessment that implements "learning by doing" principles in building automation education. His work with this consortium emphasizes practical validation of smart grid technologies and demand response systems.
Cuo Zhang is a Lecturer of Power Engineering and ARC DECRA Fellow at the University of Sydney's School of Electrical & Computer Engineering. He holds a B.E. (Hons.) from the University of Sydney (2014) and a Ph.D. in Electrical Engineering from UNSW (2018). His research focuses on smart grids, renewable energy integration, voltage control, and optimization of power systems. Key interests include distributed generation planning, energy storage systems, and demand response mechanisms. Dr. Zhang leads research on enhancing distribution network resilience through advanced control strategies and participates in the Net Zero Institute. He has secured grants such as the 2024 ARC DECRA project on renewables hosting capacity. Supervised students include Yunqing Zhang, working on robust renewables integration. His recent publications emphasize data-driven approaches, decentralized energy trading, and adaptive control for unbalanced networks. He explores machine learning applications in energy management and stochastic optimization under uncertainty. Awards include the University Medal for academic excellence. Awards: ARC DECRA Fellow Grants: 2024 Robust Renewables Hosting Capacity Enhancement Labs/Teams: Member of the Net Zero Institute
Associate Professor Archie Chapman is an Associate Professor in Computer Science and Deputy Director (Teaching and Learning) at the School of Electrical Engineering and Computer Science, The University of Queensland. His research focuses on applying artificial intelligence, game theory, optimization, and machine learning to address challenges in future power systems, including renewable energy integration and battery storage optimization. Prior to UQ, he held roles as a Research Fellow in Smart Grids at the University of Sydney (2011-2019) and a postdoc at the University of Southampton (2009-2010), where he completed his PhD in 2004. Research interests include: - Large-scale optimization for energy systems - Demand response and peer-to-peer energy trading - Renewable energy integration and grid stability - Battery storage strategies for smart grids - Algorithmic game theory for energy market design Notable projects: - Bruny Island battery trial for network congestion management - Analysis of tariff impacts on solar households - Development of decentralized energy management frameworks Publications span over 100 articles, with recent work focusing on: - Prosumer battery systems and capacity firming (2025) - Unbalanced optimal power flow benchmarks (2024) - P2P energy trading mechanisms (2021-2023) Expertise includes: - Techno-economic analysis of energy systems - Distributed optimization algorithms - Policy and market design for renewable integration
Univ.-Prof. Katja Corcoran serves as Professor of Psychology and Vice Dean for Research at the University of Graz's Faculty of Natural Sciences, leading the Institute of Psychology. She directs the university's 'Smart Regulation' profile area and participates in the 'Brain and behavior' research network, with leadership roles including former Head of Psychology Institute (2017-2019) and Deputy Head of Doctoral School of Psychology (2021-2023). Her research centers on social psychological mechanisms in sustainability transitions, particularly: Energy citizenship frameworks and prosumer behavior Goal contagion dynamics in social networks Intergroup contact interventions in educational settings Regulatory psychology for sustainable systems Recent publications (2023-2025) demonstrate interdisciplinary integration of psychological, legal, and economic perspectives, featuring field experiments across Austria and multi-lab European collaborations examining energy citizenship scales, behavioral nudges for appliance usage, and prejudice reduction in schools. Honors include: Feodor Lynen Research Fellowship (Alexander von Humboldt Foundation, 2004) She currently directs major funded initiatives: EU: 'Energy Citizenship and Energy Communities for Clean-Energy Transition' (2021-2024) FFG: 'FIWARE Driven Energy Communities for the Future' (2023-2026) International: 'Active User Participation for Smart Energy Services' (2020-2023) Corcoran serves on editorial boards of Social Psychology (since 2016) and Social Cognition (since 2013), and her work operates within the 'Brain and behavior' network fostering neuroscience-psychology-economics collaborations for complex decision-making research.
Cajsa Bartusch Kätting is a Senior Lecturer at Uppsala University's Department of Civil Engineering and Industrial Engineering within the Faculty of Science and Technology, and a Researcher at the Institute for Research on Conflicts of Goals in Sustainable Social Transition. As leader of the Uppsala Smart Energy Research Group (USER), she investigates electricity consumer and prosumer roles in smart grid development, focusing on demand response, decentralized generation, and sustainable energy transitions through industry-academic collaborations with partners including Ellevio and STUNS Energi. Her research centers on demand flexibility and consumer behavior in energy systems, examining how dynamic pricing, feedback mechanisms, and IT services influence residential and commercial electricity consumption. She integrates social psychology with engineering to design interventions for sustainable energy use, particularly studying gender differences in tariff understanding, prosumer integration challenges, and the impact of occupancy patterns on consumption. Analysis of her 15 most recent publications reveals increasing focus on behavioral aspects of smart grids, with empirical studies on dual-price signal confusion, microgrid optimization, and pandemic-driven consumption shifts. Her work consistently addresses the human dimension of energy transitions, moving beyond technical solutions to examine cognitive processes and social barriers in demand response adoption. Bartusch has secured significant funding from the Swedish Energy Agency and Familjen Kamprads stiftelse for projects like Användarnas roll i implementeringen av smarta elnät (2019-2024) and Holistiska affärsmodeller för prosumenter (2015-2018), often collaborating with municipalities and energy companies to translate research into practical solutions for grid congestion and renewable integration. She leads the USER research group which conducts applied interdisciplinary work combining engineering, psychology, and social sciences. The group's projects with partners like Uppsala Municipality and KTH focus on real-world implementation of demand response programs, prosumer business models, and microgrid optimization in multi-dwelling buildings, directly addressing Sweden's energy transition challenges.
Sandra Bellekom is a Lecturer-researcher at Hanze University of Applied Sciences, working within the Entrance – Center of Expertise Energy. Her work focuses on system integration in the energy transition, with particular expertise in renewable energy systems, solar power optimization, and smart grid technology. She contributes significantly to research projects related to sustainable energy solutions and environmental systems analysis. Education: Ph.D. in Electrical Engineering from Delft University of Technology (1993-1998) Master's degree in Energy and Environmental Sciences, cum laude, from University of Groningen (2002-2005) Basic Teaching Qualification (BKO) from University of Groningen (2010-2011) Master's degree in Electrical Engineering (ir), cum laude, from Delft University of Technology (1989-1993) Sandra Bellekom's research interests span the critical areas of energy transition and sustainable systems. Her work emphasizes practical applications of renewable energy technologies, particularly focusing on system integration challenges. She investigates how solar energy systems perform under real-world conditions, examining factors like panel contamination and cleaning effectiveness. Her research also extends to hydrogen energy systems, smart grid integration, and the economic optimization of renewable energy solutions. Through her work, she addresses key challenges in making the energy transition technically feasible and economically viable, with a strong focus on data-driven analysis and system modeling. Her recent publications (2019-2025) demonstrate a clear trend toward applied research in solar energy optimization and hydrogen systems. The research shows increasing focus on practical field studies examining how real-world factors like bird droppings, dust, and other contaminants affect solar panel performance. There's also a notable shift toward system-level analysis, particularly in hydrogen energy configuration and the integration of multiple renewable sources. Her work consistently bridges technical analysis with practical implementation considerations, making it highly relevant for industry applications. Sandra actively participates in multiple research projects including 'Effect of pollution and cleaning of solar parks,' 'Hydrogen Works,' and studies on sensible heat storage systems. Her collaborative approach is evident in her numerous co-authored publications across various energy domains. While specific mentoring relationships aren't detailed in the available information, her background includes supervising master's students during previous academic positions. Her research laboratory and team work primarily through the Entrance – Center of Expertise Energy, focusing on practical field studies and system modeling. Current projects involve monitoring solar parks across the Netherlands, developing hydrogen configuration tools, and optimizing energy storage solutions for buildings. The team employs a combination of field measurements, data analysis, and system modeling to address real-world energy challenges.
Miltos Alamaniotis is an Associate Professor and GreenStar Endowed Fellow in the Department of Electrical and Computer Engineering at the University of Texas at San Antonio (UTSA). His research focuses on applied artificial intelligence in nuclear security, smart grids, and radiation detection systems, with a particular emphasis on maritime nuclear applications and nonproliferation. Academic Appointments: Associate Professor (2023–Present), UTSA Education: Ph.D. in Applied Intelligent Systems, Purdue University Research interests include: Nuclear Security and Nonproliferation Smart Grids and Distributed Energy Systems Explainable AI for Radiation Detection Quantum Machine Learning Applications Intelligent Control of Nuclear Reactors Fuzzy Logic in Energy Management Recent publications highlight trends in AI-driven nuclear security systems, matrix profile methods for radiation anomaly detection, and quantum neural networks for thermographic image analysis. His work bridges nuclear engineering, cybersecurity, and smart city technologies. Scientific honors include: Top 0.5% ScholarGPS Ranking (2024) Best Paper Award at IEEE Texas Power and Energy Conference (2025) Luthcher Brown Fellowship (2023) GreenStar Endowment Fellowship (2023) NAE Frontiers of Engineering Symposium Selection (2023) UTSA President’s Distinguished Achievement Award (2022) He has supervised PhD students like Thanos Arvanitidis and secured over $15M in grants from DOE, NSF, and NRC for projects including the $25M NNSA Consortium. His AI Lab at UTSA collaborates with Argonne, Idaho, and Los Alamos National Laboratories.
Konstantinos Tsagarakis is a Professor at the School of Production Engineering and Management, Technical University of Crete. His office is located at Δ5.107, DPEM Building (Δ5), 1st Floor, and he can be contacted via email at ktsagarakis@tuc.gr or by telephone at +302821037252. His research focuses on interdisciplinary sustainability solutions, with primary expertise in: Circular economy implementation and policy analysis Sustainable production systems and environmental management Renewable energy integration and prosumer models Data-driven approaches to sustainability using social media analytics Industry 4.0 applications for sustainable development Analysis of his recent publications reveals three dominant research streams: 1) Advanced data mining techniques applied to sustainability metrics across social media platforms, 2) Policy and institutional analysis of circular economy frameworks in various industrial sectors, and 3) Technological enablers (IoT, AI, cloud computing) for sustainable transformation. His work consistently demonstrates methodological innovation through mixed-methods approaches combining empirical analysis with computational techniques.
Maciej Mitręga is a full Professor at the University of Economics in Katowice , serving as Head of the Department of Organizational Relations Management within the Faculty of Informatics and Communication . With an ORCID 0000-0003-4043-5589 , he has published 102 academic works and maintains a Google Scholar profile. 82 total publications 3 promoted theses 20 activities h-index 11 (Scopus), 17 (WoS) Total Impact Factor 184.268 His research focuses on business relationships, power dynamics in B2B contexts, and dynamic marketing capabilities. Recent work explores collaborative consumption through ESG frameworks and pandemic-era managerial adaptations in manufacturing sectors. His scientific contributions include: Systematic reviews on customer citizenship behavior Power play analysis in export-import relationships Networking capability frameworks Dynamic capabilities in intercultural environments As department head , he leads research initiatives in organizational relationship management and contributes to academic productivity through various publications and co-authored studies with international collaborators from Slovenia, Finland, and the UK.
Peyman Afzali Gorouh is a Postdoctoral Researcher in the Applied Power Electronic Systems group within the Faculty of Engineering and Science at Aalborg University, Denmark. His research focuses on developing innovative models for energy communities, smart grids, and renewable energy integration. Dr. Afzali's research interests span power engineering, smart grid technologies, renewable energy systems, and energy communities. His work particularly emphasizes prosumer economics, peer-to-peer energy trading, risk modeling in power systems, and energy democracy frameworks. He has developed novel approaches for optimizing energy communities while considering socio-economic-environmental factors, demand response, and uncertainty management. His recent publications (2020-2024) demonstrate a consistent focus on energy community modeling, with particular emphasis on peer-to-peer trading mechanisms, risk-constrained optimization, and multi-objective planning. His work bridges technical power system challenges with socio-economic considerations, creating integrated models that address both engineering and human aspects of modern energy systems. Dr. Afzali maintains an active research profile with numerous publications in high-impact journals including IEEE Transactions on Engineering Management, Energy and Buildings, Applied Sciences, and Sustainable Cities and Society. His research shows strong international collaboration, particularly with researchers from Iranian institutions.
Dr. Almas Shintemirov is a Research Fellow at Aalto University's Department of Electrical Engineering and Automation, specializing in robotics, control systems, and human-robot interaction. His research focuses on intelligent robotics, with emphasis on Real-time motion prediction for collaborative robots Nonlinear control algorithms for safe human-robot interaction Open-source robotic hardware design Deep learning applications in autonomous systems
