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Thomas HamacherView profile

Professor

• Urban Energy Systems
• Renewable Energy Integration
• Nuclear Fusion
• +3 more

Prof. Thomas Hamacher is a Full Professor of Renewable and Sustainable Energy Systems at the Technical University of Munich (TUM), affiliated with the TUM School of Engineering and Design. He leads the Munich Institute of Integrated Materials, Energy and Process Engineering (MEP) and previously served as Director of the Munich School of Engineering (MSE). His research focuses on urban energy systems, renewable energy integration, nuclear fusion, and energy modeling methodologies. He holds a PhD in Physics from the University of Hamburg and has extensive experience at the Max Planck Institute for Plasma Physics. Education: Studied Physics at Universities of Bonn, Aachen, and Columbia University (NY). Doctorate from University of Hamburg (1990s). Career highlights include leadership roles in energy research groups and academic administration. Research interests include fusion energy applications, decarbonization strategies, and systemic energy transitions. He is a member of the Environmental Science Center (WZU) at Augsburg University. Key research themes emphasize multi-sector energy systems, grid stability with renewables, and global energy policy. His work bridges technical innovation with socio-technical system analysis to address climate goals. Recent publications focus on digital twin applications, battery storage optimization, and hydrogen economy potentials. Active in international energy modeling collaborations like ETSAP TCP.

Pierre HaessigView profile

Researcher

• Energy Management
• Dynamic Optimization
• Stochastic Optimization
• +3 more

Pierre Haessig is a researcher and teacher at CentraleSupélec's Rennes campus, part of the Automation Team within the Rennes Institute of Electronics and Telecommunications (IETR). His work focuses on optimal energy management of storage systems (batteries) integrated with renewable energy sources like wind and photovoltaic. Research addresses uncertainties in energy inputs, such as solar variability and load fluctuations, using stochastic optimization techniques. He teaches Automation and Electrical Engineering in engineering programs. Affiliations: CentraleSupélec, IETR (Rennes) Key Research Areas: Energy Management, Stochastic Optimization, Renewable Integration, Battery Aging Models His publications (36+) explore topics like microgrid optimization, Kalman filter-based battery state estimation, and the impact of uncertainties on energy systems. He has contributed to open-source benchmarks like Solar Home 2020 and collaborated on projects involving hardware-in-the-loop testing for power electronics. His research emphasizes real-world applications in resilient energy systems and control strategies. Notable contributions include developing convex models for battery aging and advancing methods for anticipative/non-anticipative microgrid sizing. His work bridges theoretical optimization with practical implementations in energy storage and renewable integration.

• Robotics and Autonomous Systems
• Control Theory and Applications
• Wireless Sensor Networks
• +5 more

Professor Andrei Savkine is a distinguished academic at the University of New South Wales, serving as Professor and Head of Systems & Control within the School of Electrical Engineering and Telecommunications. With a PhD and MS from Leningrad State University, he has established himself as a leading researcher in robotics, control systems, and wireless networks. University: University of New South Wales School: School of Electrical Engineering and Telecommunications Department: Systems & Control Position: Professor and Head of Systems & Control Email: a.savkin@unsw.edu.au Professor Savkine's research spans robotics, control theory, and wireless communications with particular emphasis on UAV navigation, autonomous systems, and power grid applications. His work bridges theoretical control systems with practical implementations in surveillance, disaster response, and energy management. Recent publications demonstrate cutting-edge research in Reconfigurable Intelligent Surfaces (RIS), multi-robot coordination, and secure communications. Analysis of his publication record from 2023-2025 reveals a strong focus on UAV applications across diverse terrains and scenarios, with increasing integration of machine learning techniques. His work shows consistent innovation in trajectory optimization, sensor networks, and communications infrastructure, with particular attention to real-world constraints like uneven terrain and security concerns. Professor Savkine has authored numerous influential books including 'Autonomous Navigation and Deployment of UAVs for Communication, Surveillance and Delivery' (2022) and 'Wireless Communication Networks Supported by Autonomous UAVs and Mobile Ground Robots' (2022), establishing foundational frameworks for modern drone applications. His research program demonstrates significant interdisciplinary collaboration, particularly with researchers in power systems and computer science, addressing critical challenges in infrastructure resilience, emergency response, and next-generation wireless networks.

Zhenbin ZhangView profile

Professor

• High-power offshore wind energy conversion
• Motor drives
• Hybrid microgrids
• +2 more

Zhenbin Zhang is a full professor and institute director at Shandong University in Jinan, China. He holds prestigious fellowships including IET Fellow and IEEE Senior Member status, and has been recognized in Stanford University's 'Lifetime Scientific Impact List' for top 2% scientists globally. Research Focus: Renewable energy conversion systems Key Areas: Offshore wind energy, power electronics, microgrids, predictive maintenance His work spans high-power wind turbine control systems, hybrid microgrids, and intelligent power conversion technologies. Recent publications demonstrate expertise in distributed control architectures, predictive maintenance algorithms, and advanced converter topologies. Scientific accolades include: 2024: Science and Technology Innovation Award (China Power Supply Society) 2024: Gold Award, Geneva International Exhibition of Inventions 2018: National Distinguished Expert (China's 1000 Talents Program) 2017: VDE-Award-2017 (Germany) He has received multiple best paper awards and holds 25 conference best paper/presentation prizes. His research has been cited over 200 times for key works in wind energy conversion and power electronics.

Hrvoje PandžićView profile

Professor

• Power Systems
• Renewable Energy Integration
• Energy Storage Optimization
• +3 more

Hrvoje Pandžić is a Full Professor at the Department of Energy and Power Systems, Faculty of Electrical Engineering and Computing (FER), University of Zagreb. He serves as Deputy Head of the Department and is based in Room D-216. His work focuses on power systems optimization, renewable energy integration, and energy storage applications. Research Interests : Electricity market design and N-1 security criteria Optimal power flow and transmission expansion planning Battery energy storage systems and hydrogen technologies Demand response and microgrid optimization Power plant connection studies and grid impact assessments Technical Expertise : Specializes in power system operation and planning under market uncertainty Develops optimization models for hybrid systems (PV, battery, electrolyzers) Focuses on frequency control, synthetic inertia, and grid stability

Željko BanView profile

Professor

• Renewable Energy Systems
• Energy Storage
• Control Algorithms
• +5 more

Željko Ban is a Full Professor at the Department of Control and Computer Engineering, University of Zagreb, Faculty of Electrical Engineering and Computing. He is affiliated with the LARES (Laboratory for Renewable Energy Sources) , focusing on energy flow optimization, power electronics, and adaptive control systems. Research areas include microgrid optimization, regenerative braking energy management, hybrid energy storage systems, and fuel cell modeling. Professional memberships involve work on control algorithms for electric drives, renewable energy integration, and robotics applications in demining. His work spans modeling and control of DC/DC converters, energy efficiency improvements in rail vehicles, and solar irradiance prediction for photovoltaic systems. While no specific awards or student advisement details are listed, his contributions to energy storage and control systems are evident through numerous research projects and publications.

• Power Systems Planning
• Transmission Expansion Planning
• Renewable Energy Integration
• +5 more

Dr. Andrés Ramos Galán is a Full Professor at the Industrial Organization Department and Instituto de Investigación Tecnológica (IIT) of Comillas Pontifical University since 1984. His work spans power systems planning , renewable integration , and energy market modeling with a focus on stochastic optimization and Benders decomposition techniques. He has led 134 projects including DIAMOND (Horizon Europe) and ATMOSPHERE (green hydrogen modeling) and served as IIT Director (2020-2023) and MBA Director (2015-2020). His research bridges complex network analysis for grid topology and offshore wind farm layout optimization , with 21 supervised Ph.D. theses covering topics from hydrothermal scheduling to virtual power plants . Recent projects like OPEN_ENTRANCE and DEFINER address energy transition challenges. Key publications (2022-2025) demonstrate expertise in transmission expansion , storage valuation , and flexibility assessment , with a focus on Spanish and European systems. His 2025 work on CSR and grid resilience and 2023 Renewable & Sustainable Energy Reviews paper on flexibility visualization tools highlight practical applications. Students and collaborators include leading researchers in hydro modeling (S. Lumbreras), unit commitment (G. Morales-España), and network analysis (R. Espejo). Current projects involve hydrogen integration and renewable-dominated system optimization for 2030-2050 horizons.

Bill DiongView profile

Professor

• Power and Energy
• Dynamic Systems and Control
• Biomedical Engineering
• +4 more

Dr. Bill Diong is a Professor in the Department of Electrical Engineering at Kennesaw State University's College of Engineering. He transitioned from industry (UTC Aerospace Systems) to academia in 2007, focusing on power/energy systems and biomedical engineering. PhD, MS, BS in Electrical Engineering from University of Illinois (Urbana-Champaign) Research Interests include: Power electronics for electric vehicles and renewable energy integration Multilevel inverters and soft-switched DC-DC converters Arc fault detection in hybrid/electric vehicles (funded by U.S. Air Force) Dynamic modeling of respiratory impedance for asthma/COPD diagnosis Scientific Achievements : $1.25M+ in grants from Georgia DOT, NSF, EPA, Ford, and others Co-advisor for KSU Electric Vehicle team (2x International EV Grand Prix winner) 2018 KSU Outstanding Research and Creative Activity Award recipient Teaching : Courses in circuit analysis, electric machines, power conversion, and electric drives.

• Stochastic Control
• Probabilistic Modeling
• Decentralized Control Systems
• +7 more

Dr. Yuyang Zhou is a Lecturer in the School of Computing, Engineering and the Built Environment at Edinburgh Napier University, where he contributes to the Centre for Artificial Intelligence and Robotics. His research focuses on advanced control systems, probabilistic modeling, and intelligent robotics, with active involvement in EU-funded projects such as iMARS (2024–2028). Institution: Edinburgh Napier University School: School of Computing Engineering and the Built Environment Research Centre: Centre for Artificial Intelligence and Robotics Role: Lecturer Email: Y.Zhou@napier.ac.uk Dr. Zhou's research centers on stochastic and nonlinear control systems, with a strong emphasis on decentralized and probabilistic frameworks. His work integrates machine learning, entropy-based monitoring, and message-passing algorithms to enhance system performance under uncertainty. Key domains include smart grids, industrial prediction systems, and robotics. The recent publications highlight a consistent trend in developing innovative control strategies for complex stochastic systems. These include event-triggered relearning, variance and entropy assignment, and fully probabilistic design methods. The research spans applications in industrial automation, energy systems, and future grid technologies, demonstrating a strong interdisciplinary approach combining AI, control theory, and IoT. Dr. Zhou supervises postgraduate research students, including Anna Chernikova (Hybrid and Switched Control Systems) and Fatima Mumtaz (AI-driven smart banking). He collaborates extensively with Prof. Randa Herzallah and is a co-investigator on the European Commission-funded iMARS project, which aims to develop intelligent multi-agent robotic systems for first responders using AI, IoT, and 5G technologies.

Drazen DujicView profile

Associate Professor

• Power Electronics
• Medium-Voltage Systems
• Electrical Energy Conversion
• +3 more

Drazen Dujic is an Associate Professor and Head of the Power Electronics Laboratory at École Polytechnique Fédérale de Lausanne (EPFL). He holds a PhD from Liverpool John Moores University (2008) and prior industry experience at ABB Switzerland Ltd (2009–2014). His research focuses on high-power electronic systems and medium-voltage applications, including energy conversion, storage, and renewable integration. He has authored over 200 publications and 22 patents. Education: PhD in Electrical Engineering (Liverpool John Moores University, 2006–2008), MSc and Dipl.Ing. in Power Electronics (University of Novi Sad, Serbia, 1996–2005). Awards: Istvan Nagy Award (2021), EPE Outstanding Service Award (2018), Isao Takahashi Power Electronics Award (2014). Teaching: Courses include Power Electronics, Industrial Electronics, and Renewable Energy Applications. PhD Supervision: Current advisees include Amin Darvishzadeh, Max Dupont, and others; past students include Miodrag Basic and Daniel Biner. His research emphasizes medium-voltage systems, resonant converters, and grid integration technologies. Key projects include advanced DC power distribution networks and high-efficiency MVDC converters. He actively contributes to IEEE PELS committees and serves as Director of the Doctoral Program in Energy at EPFL.

• Machine Learning
• Prediction
• Data Analysis and Visualization
• +7 more

Eugenio Francisco Sánchez Úbeda is an Associate Professor at the College of Engineering, Comillas Pontifical University, and a researcher at the Technological Research Institute (IIT). He has been affiliated with the institution since 1991 and teaches Statistics, Machine Learning, and Data Analysis at ICAI. His academic and research work spans energy systems, healthcare analytics, and machine learning applications. Education: PhD in Industrial Engineering, Comillas Pontifical University, 1999 Degree in Industrial Engineering (Electronics), Comillas Pontifical University, 1991 His research interests include Machine Learning, Prediction, Data Analysis and Visualization, Nonlinear Statistical Models, and Deep Learning, with a strong focus on energy demand forecasting and probabilistic modeling. He has led numerous research projects in collaboration with major European companies such as Endesa, Enel, and Airbus. Recent publications highlight his work in energy efficiency, healthcare monitoring using wearable devices, microgrid optimization, and pandemic-related energy demand shifts. His research integrates advanced machine learning techniques with real-world applications in energy and public health. Scientific Awards and Recognition: Director of work awarded 'Premio Iberdrola al mejor Trabajo Fin de Master 2020-21' Director of work awarded 'Premio Management Solutions al mejor Proyecto Fin de Carrera 2017-18' He has advised multiple PhD students and serves on thesis committees. He is also an active reviewer for journals such as Energy Economics and Energy . His leadership extends to organizing scientific workshops like the JOSITE series and contributing to funded research projects including those under Horizon 2020 and the Inter-American Development Bank. He has delivered invited seminars on data mining, genetic algorithms, and MATLAB visualization at Comillas and other institutions, and has participated in over 100 research projects in energy and data science.

Dirk JordanView profile

Researcher

• Photovoltaics
• Renewable Energy Engineering
• Degradation Mechanisms
• +4 more

Dirk Jordan is a Researcher VI at the National Renewable Energy Laboratory (NREL) within the Materials Science Photovoltaics Research Topic . His work focuses on photovoltaic system reliability , degradation mechanisms , and advanced statistical analysis for energy applications. Education: PhD in Physics, Arizona State University Master in Physics, Arizona State University Bachelor in Physics, Heidelberg University of Education Six Sigma Black Belt, Motorola Research Interests include AI-driven machine learning for energy systems, extreme weather resilience , performance loss in solar infrastructure, and big data analytics applied to photovoltaics. His recent work emphasizes embedded sensors and multivariate analysis to optimize PV longevity. Research Trends: Recent publications highlight degradation rate analysis (2023), reliability in terawatt-scale systems (2022), and large-scale field data interpretation (2020-2016). Key themes include climate adaptation , quality control , and material science for photovoltaics. Scientific Recognition: 2023: NREL Distinguished Member of Research Staff 2018, 2014, 2005: NREL President's Award 2005: Scientific American Top 50 & Nanotech Briefs Top 50 Collaborates with cross-functional teams on photovoltaic module testing , weather resilience , and energy system validation . Mentions over 150 total publications with peak activity in 2023-2021.

• Microgrids
• Smart Grids
• Renewable Energy Integration
• +3 more

Dr. Pedro Palacín Farré is a Professor in the Department of Industrial Engineering at the Ramon Llull University's IQS School of Engineering. With a career spanning academia and public administration, he has held leadership roles such as General Director of Energy, Mines and Industrial Safety of the Generalitat of Catalonia (2013-2020) and Dean of the Official College of Industrial Engineers of Catalonia (COEIC) (2017). His research focuses on Microgrids, Smart Grids, renewable energy integration, and electricity sector regulation. Education: Electrical Industrial Engineer (1992), Master in Business Management (1991), Diploma in Management Development (1999), Master in Occupational Risk Prevention (2003), Doctor in Economics and Business (2005). His work emphasizes the stability analysis of microgrids using advanced techniques like modal analysis and impedance-based methods, alongside practical applications in industrial automation protocols (Profibus/Profinet). He contributes to multidisciplinary training programs at IQS, including the Degree in Industrial Technology Engineering and Master in Industrial Engineering. His research group, GEPI (Industrial Products Engineering Group), specializes in Additive Manufacturing, Reverse Engineering, and Mechanical Characterization of Materials. Collaborations span institutions like the Catalan Energy Institute (ICAEN) and Energy Research Institute Foundation of Catalonia (IREC).

Yeonho JeongView profile

Assistant Professor

• Power Electronics
• Electric Vehicles
• Renewable Energy Systems
• +3 more

Yeonho Jeong is an Assistant Professor in the Department of Electrical, Computer, and Biomedical Engineering at the University of Rhode Island and leads the URI Power Electronics Lab . His research focuses on high-performance power converters for electric transports, AI-based design tools for power electronics, wireless power transfer, and battery self-heating. Education: Ph.D. and M.S. in Electrical Engineering from KAIST (2018, 2014) Recent research trends involve machine learning-aided power electronics design , hybrid UAV energy systems , and high-efficiency LLC resonant converters . Notable funded projects include grants from the Office of Naval Research ($500,000) and USAID ($500,000). IEEE Senior Member (2023) DOD SMART Scholarship recipient (2025) Dean’s Fellowships (2024) His lab actively advises Ph.D. students like Xueshen Zhang and Chang-Seok Kim , with recent expansions in 2025 welcoming new Ph.D., visiting, and undergraduate researchers.

• Transcranial Magnetic Stimulation
• Power Electronics
• Neural Stimulation
• +5 more

Stefan M Goetz serves as an Assistant Professor in both Psychiatry & Behavioral Sciences and Neurosurgery at Duke University's School of Medicine, and is a Faculty Network Member of the Duke Institute for Brain Sciences. His unique interdisciplinary career bridges engineering and neuroscience, with significant contributions in power electronics and transcranial magnetic stimulation (TMS) technology. Dr. Goetz's research interests center on two interconnected domains: advanced power electronics systems (including battery management, power converters, and electric vehicle technology) and neural stimulation devices (particularly TMS applications). His work demonstrates how engineering innovations can directly address challenges in neuroscience and medical applications. His educational background includes a Ph.D. from Technical University of Munich, School of Medicine (Germany) completed in 2012. His extensive publication record shows remarkable productivity across both IEEE power electronics journals and neuroscience/medical journals, with numerous high-impact papers published through 2025. The research trends reveal a consistent focus on improving the efficiency, reliability, and functionality of power conversion systems while simultaneously advancing neural stimulation technology. His work on TMS devices specifically addresses challenges like acoustic noise reduction, improved targeting, and enhanced stimulation capabilities. Dr. Goetz's research program demonstrates a unique synergy between power electronics engineering and neuroscience applications, particularly in developing advanced neural stimulation devices that require sophisticated power management and conversion techniques. His dual appointment structure at Duke University reflects the institution's recognition of the value in this interdisciplinary approach to medical device innovation.