جست‌وجوی استاد و پژوهشگر

• dc-dc converters
• multi-level converters
• electric machines
• +۴ مورد دیگر

Dr. Ahmed Badawy is a Lecturer in Electrical Engineering at Lancaster University's School of Engineering, where he has been serving since 2017. His academic journey includes advanced degrees in electrical engineering and significant research experience in power electronics and renewable energy systems. Dr. Badawy's educational background includes: B.Sc. in Electrical Engineering from the Faculty of Engineering, Alexandria University, Egypt (2008) M.Sc. in Electrical Engineering from the Faculty of Engineering, Alexandria University, Egypt (2012) Ph.D. in Electrical Engineering from the Electric and Electronic Engineering Department at the University of Strathclyde, Glasgow, U.K. (2016) Dr. Badawy's research focuses on power electronics and energy conversion systems, with particular expertise in DC-DC converters, multi-level converters, and electric machines. His work emphasizes digital control of power electronic systems for applications in renewable energy integration, electric vehicles, and power quality improvement. His research has significant implications for sustainable energy systems and transportation electrification. His recent publication record demonstrates a strong focus on electric vehicle power systems, particularly modular converter topologies for on-board charging applications. There's a clear trend toward integrated solutions for EV charging that combine renewable energy sources with grid connectivity. His work also shows significant contributions to control methodologies, including model predictive control and hierarchical control systems for power electronic converters. Dr. Badawy mentors several PhD students working on cutting-edge research in power electronics and renewable energy systems. His research group is actively involved in projects related to sustainable energy conversion and electric transportation. Dr. Badawy is affiliated with Energy Lancaster and the TALOS research group at Lancaster University, where he contributes to interdisciplinary research on sustainable energy systems and power electronics applications.

• Energy Storage Systems
• High-power Power Converters
• Electrically Propelled Vehicles (Electric, Hybrid, Fuelcell)
• +۱۰ مورد دیگر

Dr. John G. Hayes is a Senior Lecturer at University College Cork (UCC) in the Department of Electrical & Electronic Engineering . He holds a Ph.D. from UCC (1998), an M.S.E.E. from the University of Minnesota (1989), an M.B.A. from California Lutheran University (1993), and a B.E. from UCC (1986). His academic career began at UCC in 2000, and he directs the Power Electronics Research Laboratory (PERL) , focusing on industrial collaborations with companies like Analog Devices and General Motors. Research Interests : Power electronics, magnetic components, electric vehicles, renewable energy systems, smart grids, and energy storage. Notable Work : Joint author of Electric Powertrain: Energy Systems, Power Electronics and Drives for Electric, Hybrid and Fuel Cell Vehicles (Wiley, 2018) and its Chinese edition (2021). Scientific Awards : 2011 IEEE William M. Portnoy Award for Best Paper/Presentation at IEEE ECCE. Advising : Supervised 10+ Ph.D. students across powertrain modeling, magnetic materials, and converter control. Current advisee: Conor Healy (Doctoral Degree). Labs : Leads PERL, which develops high-power converters for automotive and renewable energy applications, partnering with industry leaders like SMA Magnetics and United Technologies.

• Power System Protection
• Power Electronics
• High Voltage Engineering
• +۴ مورد دیگر

Michael Kleemann is an Associate Professor at the Faculty of Engineering Technology within KU Leuven , affiliated with the Department of Electrical Engineering (ESAT) . His research focuses on Power System Protection , Wireless Power Transfer , and Renewable Energy Integration , with a particular emphasis on inverter-based grid dynamics and fault analysis. Key Research Areas : Power system protection algorithms, capacitive wireless power transfer, fault location methods in medium voltage cables, and grid stability with high renewable penetration. Notable Projects : Lead projects on Protection of Future Distribution Grids (2021-2025), Capacitive Wireless Power Transfer (2020-2024), and Flux 50 ICON (2024-2026) for low-voltage DC grid protection. Publication Trends : Recent work explores capacitive wireless power transfer materials and control systems (2024-2025), fault detection algorithms for inverter-dominated grids (2023-2025), and machine learning applications in voltage regulation for photovoltaic-rich networks (2024). Teaching : Courses include Power System Protection (JPI322), Power Electronics (JPI0L8/JPI318), and Capacitive Wireless Transfer topics in graduate seminars.

Navid Bayatiمشاهده پروفایل

دانشیار

• Renewable/Hybrid Power Systems
• Protection and Transient Analysis of Power Grids
• Microgrids and Active Energy Networks
• +۵ مورد دیگر

Navid Bayati is an Associate Professor at the University of Southern Denmark, affiliated with the Institute of Mechanical and Electrical Engineering and the Centre for Industrial Electronics. He leads the Control and Protection of Smart Grids (CAP-SG) group and focuses on renewable/hybrid power systems, microgrid protection, and grid code compliance. Education: Ph.D. in Power Systems & Microgrid Protection (2020, Aalborg University); M.Sc. in Power Systems (2017, Amirkabir University of Technology) His research spans renewable energy integration , transient analysis , grid interconnection , and digital twin applications . Recent work includes machine learning for carbon emission prediction, fault localization in DC microgrids, and supercapacitor resilience in hybrid systems. Collaborations include projects like IEA Wind Task 50 and RePoSys , addressing grid renovation, life cycle assessment, and digital twin resilience. His teaching portfolio covers power electronics , energy management , and microgrid control .

Eleni Staiمشاهده پروفایل

استادیار

• Optimization
• Communications Networks
• Data Analytics
• +۴ مورد دیگر

Eleni Stai is an Assistant Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA), affiliated with the Division of Communication, Electronic and Information Engineering. She holds advanced degrees in Electrical Engineering, Mathematics, and Applied Mathematical Sciences from NTUA and the National and Kapodistrian University of Athens. Her academic credentials include: Diploma in Electrical and Computer Engineering, NTUA (2009) B.Sc. in Mathematics, National and Kapodistrian University of Athens (2013) M.Sc. in Applied Mathematical Sciences, NTUA (2014) Ph.D. in Electrical Engineering, NTUA (2015) Dr. Stai's research integrates advanced optimization techniques with communications networks and energy systems. She develops stochastic and deterministic optimization frameworks for network resource allocation, data analytics on complex topologies, and smart-grid control applications. Her work bridges theoretical foundations with practical implementations in energy-harvesting networks, network slicing, and reinforcement learning for distributed systems. Analysis of her recent publications reveals dominant research thrusts in AI-driven network management (particularly O-RAN and network slicing), energy-integrated communications, and optimization of energy communities. A significant portion of her work addresses the convergence of 5G/6G networking with power systems, emphasizing real-time control and sustainability. Her scientific contributions have been recognized through prestigious awards: Chorafas Foundation Best Ph.D. Thesis award Thomaidis Foundation Best M.Sc. Thesis award Best Paper Award at ICT 2016 Best Presenter Award at IEEE ENERGYCON 2022 Dr. Stai serves on technical program committees for major international conferences and has co-authored the book "Evolutionary Dynamics of Complex Communications Networks". She teaches undergraduate courses in Queuing Systems, Computer Networks, and Social Network Analysis, reflecting her expertise in network theory and applications. Her research trajectory demonstrates continuous evolution from fundamental network optimization to AI-enhanced solutions for next-generation communication-energy systems. Her work builds upon her postdoctoral experience at EPFL (2016-2020) and ETH Zurich (2020-2023), where she developed advanced frameworks for communications networks and energy systems.

Bruce Stephenمشاهده پروفایل

مدرس ارشد

• Data-Driven Methods
• Power Systems
• Smart Grids
• +۱۲ مورد دیگر

Bruce Stephen is a Senior Lecturer and Strathclyde Chancellor's Fellow in the Department of Electronic and Electrical Engineering at the University of Strathclyde, where he has been since 1999. His work lies at the intersection of data science and power systems engineering, with a strong focus on real-world industrial applications. His educational background includes a BSc in Aeronautical Engineering from the University of Glasgow (1997), an MSc from the University of Strathclyde (1998), and a PhD in Electronic and Electrical Engineering (2005) from the University of Strathclyde. Dr. Stephen's research centers on data-driven methodologies for solving complex engineering challenges in power systems, particularly under conditions of limited data or domain knowledge. His applications span the entire energy value chain—from generation (nuclear, wind, solar) to transmission, distribution, and end-use. He develops software solutions for condition assessment, anomaly detection, and predictive modeling to support asset management and future grid planning. Notably, he co-founded Silent Herdsman Ltd, a spin-out company applying intelligent systems to precision livestock farming. His recent publications highlight a strong trend toward advanced machine learning techniques such as transfer learning, surrogate modeling, and synthetic data generation (e.g., using CTGANs) to improve reliability and decision-making in power systems. These works emphasize explainability, uncertainty quantification, and scalability, particularly in renewable-rich and data-scarce environments. Dr. Stephen is currently the Principal Investigator on the EPSRC-funded Analytical Middleware for Informed Distribution Networks (AMIDiNe) project, aiming to identify barriers to Net Zero through improved data modeling of unmonitored networks. He has also contributed to major projects including EU FP7 ORIGIN, EPSRC APAtSCHE, AGILE, and Transactive Energy Supply Arrangements. He actively advises students and collaborates on interdisciplinary research. His professional activities include organizing the QFF Quarterly Forecasting Forum (2018) and delivering invited talks at industry workshops. He has supervised datasets and research involving structural health monitoring and industrial diagnostics. His work supports UN Sustainable Development Goals related to affordable and clean energy, industry innovation, and climate action.

Wajiha Shireenمشاهده پروفایل

استاد

• Power Electronics
• Smart Grid
• Renewable Energy Systems
• +۵ مورد دیگر

Dr. Wajiha Shireen is a Professor in the Department of Engineering Technology at the University of Houston’s College of Technology. She has held this position since 1993 and maintains a joint appointment in the Department of Electrical and Computer Engineering. Her academic focus spans power electronics, smart grid technologies, and renewable energy systems. Education: B.S. (Bangladesh University of Engineering and Technology, 1987), M.S. (Texas A&M University, 1991), Ph.D. (Texas A&M University, 1993) Dr. Shireen’s research centers on power quality, wireless power transfer, battery energy storage systems, and the integration of renewable energy sources like solar and wind into modern grids. She has pioneered advancements in MPPT control for photovoltaics and frequency regulation in microgrids , with a particular emphasis on low-inertia grid stability . Her recent publications highlight trends in EV charging infrastructure optimization , predictive control for energy systems , and grid-following battery storage operations . These works intersect electrical engineering, renewable energy, and smart grid technologies. Scientific Awards : College of Technology Outstanding Faculty Award for Teaching (2014) College of Technology Outstanding Faculty Award for Research (1998, 2006) Featured in the Journal of Engineering Technology as a leading researcher (2001) Dr. Shireen has secured over $3 million in grants from the National Science Foundation, Department of Energy, and industry partners like Texas Instruments and Transmark Subsea. She has mentored numerous students, including co-authors Amir Hussain , Preetham Goli , and Sonal Patel , and contributed to the development of educational tools such as the Microgrid Test Bench .

• Smart Grids
• Renewable Energy Integration
• Optimization of Power Systems
• +۴ مورد دیگر

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

Haibo Heمشاهده پروفایل

استاد

• Computational Intelligence
• Neural Networks
• Reinforcement Learning
• +۵ مورد دیگر

Dr. Haibo He is the Robert Haas Endowed Professor in the Department of Electrical, Computer, and Biomedical Engineering at the University of Rhode Island (URI). As an IEEE Fellow and NSF CAREER awardee, his research focuses on computational intelligence, neural networks, and reinforcement learning with applications to smart grids and microgrid systems. Ph.D. in Electrical Engineering, Ohio University, 2006 M.S. in Electrical Engineering, Huazhong University of Science and Technology, 2002 B.S. in Electrical Engineering, Huazhong University of Science and Technology, 1999 His research interests include: Computational Intelligence Adaptive Dynamic Programming Reinforcement Learning Deep Learning for Power Systems Distributed Control in Microgrids Imbalanced Data Learning Recent research trends from publications (2018-2025) show a focus on: Multi-agent reinforcement learning for energy systems Digital twin frameworks for grid security Event-triggered control mechanisms Finite-time convergence algorithms Cyber-attack resilient control systems Evolutionary computation in power networks Awards: IEEE Fellow (2018) NSF CAREER Award (2017) Dr. He leads the Computational Intelligence and Self-Adaptive Systems (CISA) Laboratory at URI, which conducts fundamental research on computational intelligence methods with applications to power systems, data mining, and neural networks.

Vijay K. Soodمشاهده پروفایل

استاد

• Power Systems
• Power Electronics
• HVDC and FACTS Controllers
• +۳ مورد دیگر

Dr. Vijay K. Sood is a Professor in the Department of Electrical, Computer and Software Engineering at Ontario Tech University. He holds a PhD in Power Electronics from Bradford University (UK), and has extensive experience in power systems, power electronics, and renewable energy integration. His research focuses on High Voltage Direct Current (HVDC) systems, Flexible AC Transmission Systems (FACTS), power electronics converters, and grid protection. He has received numerous awards, including Life Fellow of IEEE, Emeritus Fellow of the Canadian Academy of Engineers, and the 2000 IEEE Third Millennium Medal. Dr. Sood has authored/co-authored over 100 publications, including peer-reviewed articles in top journals like IEEE Transactions on Power Electronics and International Journal of Electrical Power & Energy Systems. His work addresses challenges in grid stability, renewable energy integration, and advanced control strategies for power systems. Education: PhD (Power Electronics), Bradford University, UK (1977) MASc (Electrical Machines), Strathclyde University, Scotland (1969) BSc (Electrical Engineering), Nairobi University, Kenya (1967) Awards: IEEE Third Millennium Medal (2000) Canadian Pacific Railway Engineering Award (2002) IEEE Regional Activities Board Achievement Awards (2001, 2006) His research emphasizes practical solutions for modern power systems, including HVDC controller design, synthetic inertia control for renewable grids, and advanced fault detection techniques. He has collaborated internationally on projects like the Energy System Observatory of Honduras and grid architecture models for multi-terminal DC systems.

Flavio Bezerra Costaمشاهده پروفایل

استادیار

• Smart Grid
• Renewable Energy Systems
• Power System Protection
• +۱۰ مورد دیگر

Flavio Bezerra Costa serves as an Assistant Professor in the Department of Electrical and Computer Engineering at Michigan Technological University's College of Engineering. His research focuses on critical areas of modern power systems, including smart grid technologies, renewable energy integration, power system protection, and advanced applications of signal processing and artificial intelligence in electrical power networks. Dr. Costa's research interests span a comprehensive range of power system topics with particular emphasis on Smart Grid technologies, Integration of Renewable Energy Systems, Power System Protection, Control, and Monitoring, Power Quality analysis, Power Systems and Power Electronics, AC/DC Microgrids, High-Voltage Direct Current (HVDC) Electric Power Transmission Systems, and the application of Signal Processing and Artificial Intelligence (including Machine Learning) in power systems. His work bridges traditional power engineering with modern computational techniques to address contemporary grid challenges. Analysis of Dr. Costa's recent publications reveals a consistent focus on wavelet transform applications for power system protection and monitoring, particularly in the areas of fault detection, classification, and location. His research demonstrates strong integration of machine learning techniques with traditional power system protection methods, with significant contributions to transformer protection, transmission line fault analysis, and microgrid stability. The work shows an evolving trajectory from fundamental wavelet-based protection techniques toward more sophisticated AI-enhanced approaches for modern power grid challenges. Dr. Costa maintains an active research program with numerous publications in top-tier IEEE journals and conferences, demonstrating his significant contributions to the field of power systems engineering and protection.

• Model Predictive Control
• Power Electronics
• Renewable Energy Integration
• +۵ مورد دیگر

Ricardo Aguilera Echeverria is an Associate Professor at the University of Technology Sydney (UTS), School of Electrical and Data Engineering . With a Ph.D. in Electrical Engineering from the University of Newcastle (2012), he has held academic positions at UNSW Australia (2014-2016) and UTS since 2016. His research focuses on model predictive control (MPC) applied to power electronics , renewable energy integration , and microgrid control systems . He actively supervises Masters and PhD students and has developed courses such as Control Studio A and Control Studio B . Education: PhD in Electrical Engineering (University of Newcastle, 2012) MSc in Electronics Engineering (Universidad Tecnica Federico Santa Maria, 2007) BSc in Electrical Engineering (Universidad de Antofagasta, 2003) Research Interests: Model Predictive Control (MPC) for power converters Microgrid stability and cybersecurity Second-life battery integration Hybrid DC-AC microgrid solutions Recent Research Trends: Advancements in modular multilevel matrix converters (M3C) for LFAC systems Development of per-phase instantaneous power theories for LVRT compensation Sliding mode observers (SMO) for cyberattack mitigation in AC microgrids Optimal control strategies for delta-connected CHB converters in energy storage Grants & Projects: Lead investigator in HORIZON Europe (2024-2027) on digital solutions for renewable energy systems ARC Discovery Project (DP240102646) on extending second-life battery life (2024-2026) Collaborative grants with Sovereign Propulsion Systems Pty Ltd and NSW Department of Industry for hybrid-electric vehicle control

Eduard Muljadiمشاهده پروفایل

استاد

• Power Systems
• Power Electronics
• Electric Machines
• +۵ مورد دیگر

Eduard Muljadi is the Danaher Professor in the Department of Electrical and Computer Engineering at Auburn University. He holds a Ph.D. in Electrical Engineering from the University of Wisconsin and a B.S. from Sepuluh Nopember Institute of Technology. His research focuses on power systems resilience, renewable energy integration, electric machines, and grid stability. Key areas include microgrid reliability, inverter-based resource control, and the optimization of renewable energy systems. Recent work emphasizes grid-forming inverters, hybrid AC/DC microgrids, and the impact of high renewable penetration on power quality and stability. His studies on cogging torque reduction in permanent magnet machines and thermal management of induction motors highlight his expertise in electric machine design. Muljadi also explores advanced pumped storage hydropower technologies and their role in stabilizing grids with high renewable integration. Publications from 2024-2025 reveal trends toward mitigating oscillations in power grids, enhancing frequency response via BESS coordination, and analyzing fault contributions of inverters. His research bridges theoretical advancements with practical grid solutions, such as optimizing wind farm layouts and improving protection systems in modern distribution networks.

Taehyung Kimمشاهده پروفایل

دانشیار

• Power Electronics
• Motor Drives
• Automotive Engineering
• +۳ مورد دیگر

Taehyung Kim is an Associate Professor at the University of Michigan-Dearborn in the Department of Electrical and Computer Engineering , College of Engineering and Computer Science. His research focuses on power electronics , motor drives , and electric/hybrid power systems for vehicles and aircraft , with an emphasis on renewable energy integration and fault-tolerant control . Education Ph.D., Electrical & Computer Engineering, Texas A&M University M.S., Electrical Engineering, Korea University B.S., Electrical Engineering, Korea University His research interests include energy conversion systems, power electronics for electric vehicles, evaluation and diagnosis of AC motors, and position sensorless control of permanent magnet motors. He leads the KIM Laboratory , which explores unmanned aerial vehicles (UAVs) , battery systems , and powertrain reliability . The 15 most recent articles (2024-2021) highlight his work on hybrid UAVs , fault detection algorithms , cost-effective converters , and powertrain optimization . These publications span power electronics , renewable energy integration , and electric propulsion systems , with applications in transportation electrification and industrial power systems . Scientific Awards NSF Mid Career Advancement Award, 2023 IEEE-IAS Prize Paper Award (2nd Place), 2012 Best Paper Award, IEEE Transportation Electrification Conference, 2021 Listed in "World Top 2% Scientists" (Stanford University, 2020-2024) Listed in Marquis Who’s Who in America Technical Program Co-Chair, 2009 IEEE Vehicle Power and Propulsion Conference Prof. Kim has advised numerous PhD and Master’s students , including Feng Zhou , Sreekanthreddy Chalapala , and Sahithya Parvathareddy . He has secured significant grants from the NSF , Department of Energy , and industry partners like Ford, focusing on smart monitoring , fault identification , and energy management for electrified systems. His lab’s facilities include advanced power electronics labs and hybrid powertrain testing environments .

Wenjuan Songمشاهده پروفایل

مدرس

• Net-zero transition in transport
• Aviation electrification
• High-speed rail electrification
• +۴ مورد دیگر

Dr. Wenjuan Song is a Lecturer in Electrically Powered Aircraft, Propulsion, Electrification & Superconductivity Group at the James Watt School of Engineering, University of Glasgow. She holds a PhD in Electrical Engineering from Beijing Jiaotong University (2019) and has held postdoctoral positions at Victoria University of Wellington (2016–2018) and the University of Bath (2019–2021). Her research focuses on accelerating net-zero transitions in transport sectors through superconductivity and AI-driven solutions. Research Interests: Net-zero aviation, renewable energy systems, superconducting fault current limiters, cryogenic systems, and AI applications in electrification. Awards: Global Talent (UK Royal Academy of Engineering, 2021), featured in IEEE PES Women in Power, and COST Action publications. Teaching: Course coordinator for Simulation of Engineering Systems, Simulation of Aerospace Systems, and Power Engineering 3. Professional Activities: Organizing Committee member (UK Fluids Conference 2023), guest editor (Superconductor Science and Technology), and session chair at international conferences. Her work integrates superconductivity and AI to address challenges in electric aircraft, high-speed rail, and marine electrification. Key contributions include fault detection systems for HTS components and predictive modeling of superconducting materials.