Giovanni PETRONE is a Full Professor at the University of Salerno's Department of Information and Electrical Engineering and Applied Mathematics (DIEM). His research focuses on renewable energy systems, power electronics, and control engineering, with a strong emphasis on photovoltaic technology and energy conversion. He holds an office at Fisciano Campus, Building E, Room 058. His work includes advancements in maximum power point tracking (MPPT) controllers for photovoltaic systems, innovative inverter designs, and photocatalytic purification technologies. His patents address energy efficiency and grid integration challenges in renewable systems. He collaborates with institutions via Erasmus+ programs and has licensing agreements with companies like Matrix s.r.l. His contributions span both theoretical and applied research in sustainable energy solutions.
Américo Vicente Teixeira Leite is an Assistant Professor at the School of Technology and Management (ESTiG) of the Polytechnic Institute of Bragança (IPB), where he has been since 1994. His expertise spans Electronics, Power Electronics and Converters, Electrical Drives, Photovoltaic Systems, and Simulation. He has held leadership roles including Vice-Dean of ESTiG-IPB, President of the Scientific Council, and Coordinator of the Electrical Engineering Department. Leite has authored/co-authored over 50 publications and holds a National Invention Patent for a low-cost IV tracer for photovoltaic modules. He has participated in 8 international and 5 national research projects, focusing on renewable energy systems, microgrids, and smart grid technologies. His research interests include energy efficiency, sustainable infrastructure, and IoT-based environmental monitoring. Notable projects include the implementation of smart microgrids in cultural heritage sites (e.g., the Silk House museum) and the development of low-power photovoltaic water pumping systems. Leite’s work often bridges theoretical advancements with practical applications, emphasizing real-world deployment in renewable energy systems. His publications reflect a strong focus on grid integration of small-scale hydropower, MPPT algorithms for solar systems, and inverter control strategies. Awards include a National Invention Patent for his IV tracer device, which aids in photovoltaic module diagnostics. Leite has also contributed to educational initiatives, such as project-based learning in engineering, and has supervised three academic projects.
Assoc. Prof. Dr. Kadir Vardar is an Associate Professor at the Department of Electrical and Electronics Engineering, Faculty of Engineering, Dumlupınar University. He has held academic and administrative roles since 2012, including Vice President of Department (2015–2019). His research focuses on power electronics, embedded systems, renewable energy, and neural network applications in control systems. Education: BSc (2001) and MSc (2004) from Dumlupınar University; PhD (2011, English Program) from Dokuz Eylül University. Projects: Over 15 projects, including TÜBİTAK-funded initiatives on smart home automation, PV inverters, and embedded HIL simulators. Awards: 2011 Dokuz Eylül University Doctoral Publication Honor Award; 2001 Department First Place at Dumlupınar University. Research interests span power electronics (inverters, active filters), renewable energy systems (PV), and embedded systems (STM32, microcontrollers). He has published 29 articles and supervised multiple theses. Current courses include Power Electronics, Advanced Microcontrollers, and System Programming.
Farzaneh Bagheri is an active Assistant Professor in the Department of Electrical and Electronics Engineering at Antalya Bilim University, Turkey, since 2021, following her Research Assistant role at the same institution in 2019. She holds a Ph.D. from Eastern Mediterranean University (2019), M.Sc. from Azarbaijan Shahid Madani University (2010), and B.Sc. from Shahid Beheshti University (2005), all in Electrical and Electronics Engineering. As an IEEE and Industrial Electronics Society (IES) member, she serves as a regular reviewer for IEEE, Elsevier, and MDPI journals. Her educational background demonstrates a consistent focus on power engineering: Ph.D. in Electrical and Electronics Engineering, Eastern Mediterranean University, Cyprus (2019) M.Sc. in Electrical and Electronics Engineering, Azarbaijan Shahid Madani University, Iran (2010) Bachelor's in Electrical and Electronics Engineering, Shahid Beheshti University, Iran (2005) Research interests center on power electronics control systems with emphasis on power inverter control , microgrid stability , renewable energy management , and laboratory validation . Her work bridges theoretical control design with industrial applications, particularly in grid-tied systems for solar and wind energy conversion under unstable conditions. Publication trends (2021–2025) reveal deep specialization in sliding mode control variants applied to photovoltaic inverters, dynamic voltage restorers, and battery chargers. Key themes include chattering reduction, grid distortion resilience, and multi-level converter topologies for renewable integration, with increasing focus on AI-driven fault diagnosis and digital twin modeling in her 2025 output. Scientific awards are not explicitly listed in the source material. She contributes to European and national research/industrial projects in power systems and power electronics, though specific grant details are omitted. No student advising roles are documented, but her faculty position suggests graduate mentorship responsibilities. Laboratory validation work implies hands-on experimental leadership. Her IEEE/IES membership and journal reviewing activities indicate active participation in professional communities. Experimental research is conducted within power electronics laboratories, with recent projects emphasizing solar plant integration and AI maintenance tools.
Clara Marina Sanz Garcia is an Associate Professor in the Electronic Technology Department at Charles III University of Madrid (UC3M). She is a member of the Electronic Power Systems Group (GSEP) and teaches courses in Electronics, Mechanical Engineering, and Telecommunications. Her research focuses on power electronics with applications in photovoltaic systems, electric vehicles, and aerospace power systems. Dr. Sanz Garcia's research spans multiple critical areas of power electronics including DC-DC converters, photovoltaic systems integration, solid-state power controllers, and impedance modeling. Her work demonstrates particular expertise in converter topologies for renewable energy applications, with numerous publications on specialized converter designs like the AFZ converter, autotransformer forward-flyback converter, and Buck-Boost Modified Series Forward converter. She also has significant contributions in hardware-in-the-loop simulation techniques and digital control implementations using FPGAs. Her recent publications reveal a strong trend toward practical implementation of power electronic systems with a focus on stability analysis, control strategies, and system integration. The research consistently bridges theoretical modeling with practical applications, particularly in renewable energy systems and transportation electrification. Many of her papers address the challenges of integrating power electronic converters into larger systems, with special attention to stability issues that arise in cascaded converter architectures. Convertidor CC-CC reductor y elevador, método de conversión CC-CC, y planta fotovoltaica que incorpora dicho convertidor (2019) Active control procedures for the connection of very capacitive loads using SSPCs (2017) Active control procedures for the connection of very capacitive loads using SSPCs (2014) Método y dispositivo de transformación de corriente continua en corriente alterna (2014) Método y sistema de alimentación de una carga constituida por una pluralidad de cargas elementales, en particular de LED (2013) Dr. Sanz Garcia has supervised at least one doctoral thesis on novel converter families for photovoltaic applications and has been principal investigator on multiple research projects including 'Estrategias de modelado y control para la estabilización de la InterCONEXión de convertidos electrónicos de POTencia' (2018-2021) and 'SMARTMOD-Habilitación de funciones inteligentes en convertidores de potencia modulares para la movilidad eléctrica' (2022-2025). She has secured funding from diverse sources including the Ministry of Economy, European Commission, and industry partners like Siemens Healthcare. She leads research within the Electronic Power Systems Group (GSEP), focusing on power converter design, stability analysis, and applications in renewable energy systems and transportation electrification. Her team works on both theoretical modeling and practical implementation, with strong connections to industry applications in aerospace, railway systems, and medical equipment.
Evangelos E. Milios is a Professor in the Faculty of Computer Science at Dalhousie University , Halifax, Nova Scotia. He has been a faculty member since 1998 and leads the MALNIS (Machine Learning and Networked Information Spaces) research group. He is affiliated with the Institute of Big Data Analytics and served as Scientific Director of DeepSense , an innovation hub for ocean data analytics. Education: PhD in Electrical Engineering and Computer Science, MIT (1986) SM & EE, MIT (1983) Dipl. Eng. in Electrical Engineering, NTUA, Greece (1980) His research focuses on visual text analytics, text mining, graph mining, social network analysis, and machine learning . He has made significant contributions to modeling and mining of networked information spaces, with applications in data science and AI. The recent publications reflect a strong trend in data mining, robotics, pattern recognition, and semantic analysis , particularly in log analysis, pose estimation, and information retrieval. His work bridges theoretical algorithms with practical applications in robotics and web technologies. Scientific Awards and Honors: Distinguished Research Professor (2017–2022) Killam Chair in Computer Science (2006–2011) Senior Member, IEEE Professional Engineer, Ontario (1998–2024) He has served in key administrative roles including Associate Dean, Research (2008–2017) and Director of the Graduate Program (1999–2002) . He has supervised numerous graduate students and taught a wide range of courses in AI, machine learning, data science, and networking. His research is supported by major grants and collaborations, including NSERC and industry partnerships. Research Labs and Teams: MALNIS – Focuses on machine learning and networked information spaces. DeepSense – Ocean data analytics and AI innovation. Institute of Big Data Analytics – Cross-disciplinary big data research.
Cristina MOREL is a Permanent lecturer-researcher at ESTACA since 2020, specializing in electrical engineering and control systems. Previously, she held academic positions at ESEO (2016-2020) and the IUT of Angers (2000-2020), and began her career at the Technical University of Cluj-Napoca (1992-1999). Her research focuses on nonlinear dynamics, chaos control, and applications in power electronics and renewable energy systems. Dr. MOREL holds a Doctorate in Automatics and Applied Computer Science from the University of Angers (2005) and a Habilitation to Direct Research (2016). She earned her Graduate Engineer degree in Automation and Computer Science from the Technical University of Cluj-Napoca (1992), where she was Vice-major of her promotion. 2016: Habilitation to Direct Research in Electronics, University of Angers 2005: Doctorate in Automatics and Applied Computer Science, University of Angers 1992: Graduate Engineer in Automation and Computer Science, Technical University of Cluj-Napoca Her research spans chaos control , nonlinear dynamics , and their applications in power electronics and renewable energy systems . She pioneered anticontrol of chaos to reduce electromagnetic interference in power converters and developed novel maximum power point tracking (MPPT) algorithms for photovoltaic systems under partial shading. Current work focuses on fault diagnosis for electric vehicle powertrains using entropy analysis and neural networks. Recent publications (2022-2025) show strong focus on chaos applications for MOSFET thermal management, entropy-based fault diagnosis in inverters, and energy storage optimization for electric vehicles and drones. There is clear evolution toward data-driven approaches (neural networks) for fault detection and real-world applications in e-mobility. Dr. MOREL has received several academic honors early in her career: Winner of the National University Assistant Competition (Romania, 1996) Winner of the National University Preparation Competition (Romania, 1993) Winner of the national entrance exam to the Polytechnic School of Cluj-Napoca (1987, 15th out of 700 candidates) She has supervised five PhD theses and three Master's research projects on topics including fault diagnosis in polyphase machines, energy management for battery-ultracapacitor vehicles, and MPPT for photovoltaic systems. Her research is supported by collaborations with University of Angers, ESEO, and ESTACA laboratories. Dr. MOREL led the Automation and Electrical Engineering research group at ESEO (2016-2018) and the Energy and Environment option (2016-2020), conducting experimental work in power electronics and control systems laboratories focused on converter design and EV powertrain validation.
Associate Professor Dušan Medved serves at the Department of Electrical Power Engineering within the Faculty of Electrical Engineering and Informatics at the Technical University of Košice. As Head of the Electricity Generation and Distribution Department, he plays a key leadership role in shaping electrical engineering education and research at the institution. His extensive teaching portfolio spans fundamental electrical engineering concepts through to specialized topics in power systems and renewable energy technologies. Medved's research interests primarily focus on power system modeling, renewable energy integration, and smart grid technologies . His work demonstrates particular expertise in photovoltaic systems, electric vehicle integration, electromagnetic field analysis, and power quality assessment. He has developed significant expertise in using EMTP-ATP software for power system transient analysis and has published extensively on modeling techniques for electrical power engineering applications. An analysis of his recent publications (2023-2024) reveals a strong emphasis on the integration of renewable energy sources into power grids, with particular attention to photovoltaic systems, electric vehicle charging infrastructure, and energy storage solutions. His work bridges theoretical modeling with practical implementation challenges, addressing critical issues such as grid stability during high renewable penetration, optimal sizing of energy storage systems, and maximizing self-consumption of locally generated renewable energy. The interdisciplinary nature of his research connects electrical engineering with energy economics and environmental considerations. Medved has been actively involved in teaching a wide range of courses including Fundamentals of Electrical Engineering, Electrothermal Technology, Electrical Energy Transformations, and Modeling in Electrical Power Engineering. His teaching materials demonstrate a hands-on approach with practical assignments covering resistance furnace design, arc steelmaking furnace analysis, and power system modeling using EMTP-ATP software. His commitment to education is evident in his development of numerous teaching resources and student projects spanning from 2012 to the present.
Idriss Dagal serves as an Assistant Professor at Beykent University's Department of Electrical and Electronics Engineering. With a PhD and Master's in Electrical Engineering from Yildiz Technical University (2015 and 2023 respectively), and additional academic credentials from Ethiopian Airlines Aviation University and Mongo Polytechnics University, his career bridges academic research with industry experience as a Sales Engineer. PhD: Yildiz Technical University (2015) Master's: Yildiz Technical University (2023), Ethiopian Airlines Aviation University (2008) Bachelor's: Mongo Polytechnics University (2006) His research focuses on renewable energy systems , particularly photovoltaic power optimization using metaheuristic algorithms (Hybrid PSO-Salp Swarm, Gray Wolf Optimization). He also explores control systems for solar energy and aircraft dynamics, including PID and fuzzy logic controllers. Additional work spans machine learning applications in energy and medical diagnostics, along with power electronics for battery charging. Recent publications highlight 15 2025 articles on topics like hybrid energy systems , AI-driven MPPT , and aircraft control frameworks . His work appears in journals such as Scientific Reports , IEEE Access , and International Journal of Aeronautical and Space Sciences . Teaching experience includes courses in Electrical Machines and Information Technologies . Non-university roles at Elektra Electronic Company and Aktif Group Company involved sales engineering, complementing his academic profile with industry insights.
Mauricio Muñoz Arias is an Assistant Professor at the University of Groningen's Faculty of Science and Engineering, affiliated with the Engineering Systems and Design Group. His research focuses on developing and applying port-Hamiltonian control theory across multiple domains including aerospace systems, renewable energy, robotics, and sustainable technologies. Research interests span satellite attitude control, CubeSat design for Earth observation, energy optimization for wave energy converters, and control strategies for solar-powered systems. His work integrates theoretical developments with practical applications in mechanical systems and biological systems modeling. Publications demonstrate strong emphasis on energy-based approaches across renewable energy systems, aerospace control, and robotic applications. Recent work shows increasing focus on sustainable technologies and interdisciplinary applications combining control theory with biological systems.
Toru Tanzawa is a Professor at Waseda University's Faculty of Science and Engineering, Graduate School of Information, Production, and Systems. He holds a Ph.D. from the University of Tokyo (2002) and maintains an active research laboratory focused on power electronics and energy harvesting systems. His professional memberships include IEEE and IEICE, and he has served on various technical committees including the IEICE Electronics Society's Integrated Circuit Research Committee and the IEEE ESSCIRC Technical Program Committee. Professor Tanzawa's research focuses on low-power analog circuits , energy harvesting , greening of integrated circuits , IoT systems , power management , and circuit design . His work bridges theoretical circuit analysis with practical implementations for real-world applications, particularly in memory systems and energy-constrained environments. He has pioneered numerous innovations in switched-capacitor converters, charge pump circuits, and power management solutions for NAND flash memory and IoT devices. His publication record shows a clear progression from fundamental circuit theory to practical implementations, with recent work focusing on energy harvesting from thermoelectric generators, microwave wireless power transfer, and ultra-low-voltage operation. The research demonstrates consistent innovation in power conversion efficiency, particularly in the 1-100 μW range relevant for IoT applications. His publications span top venues including IEEE journals and conferences like VLSI Symposium. Test of Time Award, Symposium on VLSI Technology and Circuits (2023) IEEE Fellow (2016) Professor Tanzawa leads an active research group with numerous industry collaborations. His current research projects include "Understanding the operation principle of boost converters from extremely low voltage and application to IoT terminals" (2022-2025), funded by the Japan Society for the Promotion of Science. He has also secured multiple patents related to power conversion circuits and rectenna systems. His laboratory maintains strong connections with semiconductor industry leaders, particularly in memory technology and power management ICs.
Dr. Ruiyun Fu serves as Assistant Professor in the Department of Electrical and Computer Engineering within Mercer University's School of Engineering. Her expertise spans power electronics, renewable energy systems, and semiconductor device modeling. Education: PhD in Electrical Engineering, University of South Carolina (2013) MS in Electrical Engineering, Huazhong University of Science and Technology (2007) BS in Electrical Engineering, Huazhong University of Science and Technology (2004) Her research focuses on power semiconductor device modeling (particularly SiC-MOSFET & GaN-FET), grid-connected power converters , renewable energy conversion systems , and high-frequency resonant inverters . She has developed innovative approaches for DC network protection using Z-source circuit breakers and advanced wireless power transfer techniques. Analysis of her 15 most recent publications reveals strong emphasis on DC power network security (33% of articles), semiconductor device modeling (27%), and wireless power transfer optimization (20%). The work demonstrates consistent progression from fundamental device modeling toward grid integration challenges, with increasing focus on cybersecurity aspects in recent years. Dr. Fu maintains active leadership in professional societies including IEEE Power Electronics Society, IEEE Industry Applications Society, and IEEE Women in Engineering. She serves as regular reviewer for multiple IEEE transactions and conferences including ECCE, APEC, and PES-GM. Her educational contributions include pandemic-responsive laboratory adaptations and STEAM outreach initiatives for women, reflecting commitment to both technical innovation and engineering education advancement.
Dr. Yang Du is a Senior Lecturer at James Cook University (JCU) in Cairns, Australia, specializing in Electronic Systems and IoT Engineering. He holds a Ph.D. in Electrical Engineering from The University of Sydney (2013) and has held academic positions at Xi'an Jiaotong-Liverpool University (2014–2018) and a visiting scientist role at MIT (2018). His research focuses on renewable energy systems, solar forecasting, and smart grid technologies. He has been recognized in the World’s Top 2% Scientists List by Stanford University and has authored numerous publications in top-tier journals. Education: Ph.D. in Electrical Engineering, The University of Sydney, Australia (2013) Postdoctoral Research Fellow at Masdar Institute of Science and Technology, UAE (2013–2014) Dr. Du’s research interests revolve around optimizing renewable energy integration, particularly in photovoltaic systems, energy storage, and advanced control strategies using machine learning. His work emphasizes predictive modeling for solar power ramp-rate control, federated learning frameworks for distributed energy systems, and the application of AI in IoT-driven energy management. Recent projects include ADMM-LSTM frameworks for load forecasting and thermal analysis of power devices. His publications highlight contributions to energy forecasting, grid stability, and adaptive control mechanisms. Notable achievements include developing solar forecasting models using GANs and sky images, and exploring peer-to-peer energy trading mechanisms with penalty adaptations. He actively collaborates with institutions like MIT and maintains an honorary position at Xi’an Jiaotong-Liverpool University. Dr. Du’s work addresses challenges in energy systems, such as mitigating PV power fluctuations and enhancing grid resilience through predictive analytics. His research has practical applications in microgrids, energy storage optimization, and sustainable power distribution. He has been awarded 33 academic accolades, including recognition for his impactful contributions to renewable energy research.
William Stanchina is a Professor in the Department of Electrical and Computer Engineering at the University of Pittsburgh’s Swanson School of Engineering. His research focuses on semiconductor devices, including compound semiconductors, high-frequency electronics, and power electronics. He has developed novel heterojunction devices and transitioned R&D into production for government and commercial applications. His work includes wide bandgap semiconductors for smart grid and biomedical instrumentation, as well as nanowire growth for device implementation. Dr. Stanchina holds a PhD and MSEE in Electrical Engineering from the University of Southern California (1973–1978) and a BS in Electrical Engineering from the University of Notre Dame (1971). His research emphasizes semiconductor materials growth, IC fabrication processes, and device characterization. He has established an electronic device measurement capability at Pitt to extract equivalent circuit models for semiconductor devices. His publications span GaN-based power converters, nanofabrication techniques, and optoelectronic pathogen detection systems. Recent work explores high-power-density modular converters and linear models for wide bandgap semiconductor circuits.
Jianwen MENG serves as an Assistant Professor at ESTACA, where he has been an Enseignant-chercheur (Teacher-Researcher) since 2020. He is affiliated with ESTACA'Lab, the institution's research laboratory focused on embedded energy systems and transportation technologies. His academic foundation includes a PhD in Electrical Engineering from Université Paris-Saclay (2020), a Master's degree in Electronic Systems and Electrical Engineering from the University of Nantes (2017), and a Bachelor's degree in Electrical Engineering and Automation from Jimei University, China (2015). Dr. MENG specializes in fault diagnosis, fault tolerant control, and energy management systems for electric vehicles and embedded applications. His research integrates advanced control theory with machine learning to address critical challenges in battery and fuel cell technologies, particularly focusing on state estimation, degradation prediction, and real-time monitoring under operational stress. Analysis of his recent publications (2024-2025) reveals a strong interdisciplinary trajectory blending electrical engineering with artificial intelligence. Key trends include AI-enhanced battery state estimation under fast-charging conditions, reinforcement learning for energy management in hybrid vehicles, and novel fault diagnosis frameworks for electrochemical systems. His work consistently targets practical implementation in automotive applications while advancing theoretical control methodologies. He received the Best Paper Award at the IEEE Prognostics and System Health Management Conference (PHM-Paris) in 2019 for his contributions to lithium-ion battery monitoring. At ESTACA, Dr. MENG teaches multivariable systems, real-time control, rapid prototyping, and advanced simulation tools across multiple engineering program levels. His pedagogical approach emphasizes hands-on implementation of theoretical concepts in embedded systems. As a core member of ESTACA'Lab, he contributes to cutting-edge research in automotive electrification, particularly through projects involving battery management systems, fuel cell degradation modeling, and fault-tolerant control architectures for next-generation electric vehicles.
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