Dr. King Man Siu is an Assistant Professor in the Department of Electrical Engineering at the University of North Texas, College of Engineering. He established the Power Electronics and Renewable Energy (PERE) Lab in February 2022, focusing on power electronics technologies for renewable energy, smart grids, and electric vehicle applications. University: University of North Texas School: College of Engineering Department: Electrical Engineering Research Interests: Dr. Siu specializes in power electronics, renewable energy systems, and smart grid technologies. His work addresses challenges in: Efficient energy conversion for solar and battery systems Grid integration of electric vehicles and renewable sources Advanced inverter design for residential and industrial applications Reduction of magnetic components in power converters Reactive power management and circuit breaker development Modular solutions for DC distribution and rural electrification Publication Trends: His research emphasizes optimizing power electronics through innovative topologies (e.g., Manitoba inverters, interleaved totem-pole converters) and materials (e.g., SiC MOSFETs). Key areas include energy efficiency in photovoltaic systems, smart grid stability, and DC microgrid interconnection strategies. Contact: Email: Kingman.Siu@unt.edu Office: Discovery Park B233
Sri Kolla, Ph.D. is a tenured Professor in the Department of Electronics and Computer Engineering Technology at Bowling Green State University (BGSU) , where he has served since August 2002. He also served as a Visiting Professor at the Indian Institute of Science (2017) and as a Fulbright Research Scholar (2008-2009). His academic career spans faculty roles at Penn State University, University of Toledo, and consortium graduate faculty at Indiana State University. Education: Ph.D. in Electrical Engineering and Computer Science (University of Toledo, 1989) M.S. in Electrical and Computer Engineering (University of Saskatchewan, 1986) M.E. in Electrical Engineering (Indian Institute of Science, 1983) B.E. in Electrical Engineering (Andhra University, 1981) Research Interests: Dr. Kolla specializes in Electrical Power and Energy Systems with Smart Grid applications, Control Systems for networked environments, and Machine Learning techniques for power system diagnostics. His work focuses on fault detection in microgrids using LSTM networks, stability robustness of discrete-time systems, and multi-agent protection schemes for power infrastructure. Scientific Contributions: Developed robust control frameworks for microgrid systems under parameter variations (2023-2025) Pioneered AI-based fault identification in induction motors and transformers (1995-2000) Advanced networked control system designs addressing time delays (2002-2012) Published 82+ technical articles in IEEE, ISA Transactions, and conference proceedings Honors and Recognition: Recipient of the Fulbright-Nehru Academic and Professional Excellence Award and Whiteford Scholarship . Senior member of IEEE and ISA , with listings in Marquis Who’s Who and fellowships in The Institute of Engineers (India) .
Dr. Kaushik Rajashekara is a Distinguished Professor of Engineering at the University of Houston, affiliated with the Department of Electrical & Computer Engineering. He holds leadership roles in academic and industry research, including prior positions at the University of Texas at Dallas, Rolls-Royce, and Delphi Corporation. His expertise spans power electronics, transportation electrification, and renewable energy systems. Education: MBA, Indiana Wesleyan University, 1992 Ph.D., M.S., B.S. in Electrical Engineering, Indian Institute of Science, 1984, 1977, 1974 B.S. in Science & Maths, Bangalore University, 1971 Research Interests: Power electronics and drive systems, subsea electrical systems, electric/hybrid vehicles, aircraft electrification, renewable energy, and microgrids. His work emphasizes sustainable energy solutions and advanced propulsion technologies. Awards: 2022 Global Energy Prize (highest international energy award) Member of U.S. National Academy of Engineering (2012) IEEE Medal for Environmental and Safety Technologies (2021) Multiple fellowships from IEEE, NAI, and SAE Grants & Advising: Extensive industry collaborations, including roles as Chief Technologist at Rolls-Royce and Chief Scientist at Delphi. His research focuses on cutting-edge technologies like flying cars and subsea power systems. Labs/Teams: Active in the PEMSEC lab at UH, advancing power electronics and energy systems. Collaborates globally on projects like offshore renewable energy integration and aircraft electrification.
Anh Tuan Le is an Associate Professor at the Department of Electrical Engineering, Chalmers University of Technology. He holds a PhD in Power Systems from Chalmers (2004) and a Master's in Energy Economics from the Asian Institute of Technology (1997). Specializes in power grid planning, electricity market modeling, and renewable energy integration Active in electric vehicle-grid interaction and battery storage systems Develops voltage stability solutions and decentralized control strategies His recent research focuses on: Flexibility markets for congestion management Machine learning applications in load forecasting Real-time security margin control using AI Key projects include: DigiRES (2024-2027): Digital integration of multi-energy flexibility POTENT-X (2024-2027): Port energy transition hubs FLEXIGRID (2019-2023): Distribution grid flexibility solutions
Dr. Shahab Mehraeen is a Professor and holder of the Newton B Thomas Professorship in the Division of Electrical and Computer Engineering at Louisiana State University's College of Engineering. He directs the Renewable Energy and Smart Grid Laboratory, focusing on power systems stability, renewable energies integration, smart grid technologies, energy conversion, and nonlinear/adaptive/decentralized control systems. His research explores innovative solutions for modern power grids, including hybrid AC-DC systems, microgrid stability, and advanced protection mechanisms. He has developed experimental testbeds like the IEEE 14-bus power system and DC microgrid setups for validating control algorithms. Dr. Mehraeen's publications demonstrate consistent focus on renewable integration, grid protection, and smart grid innovations with recent emphasis on DC circuit breakers and co-simulation techniques. His work integrates theoretical development with practical implementation. Research Areas Power systems stability and control Renewable energy grid integration Smart grid technologies Microgrid design and optimization Advanced circuit protection systems Awards and Recognition National Science Foundation CAREER Award recipient Holder of a US patent for infrastructure inspection and rehabilitation Research Team Leads a team of 11 graduate students working on projects related to power systems, renewable energy integration, and smart grid technologies.
Dr Brandon M Grainger is an Eaton Faculty Fellow and Associate Professor of Electrical and Computer Engineering at the University of Pittsburgh’s Swanson School of Engineering, where he also directs the Electric Power Technologies Laboratory, serves as Associate Director of the Energy GRID Institute, and co-directs Pitt AMPED. A key architect of Pitt’s electric power program since 2008, he focuses on advanced power conversion, high-voltage electronics, wide-band-gap semiconductors, and aerospace power systems. Education PhD, Electrical Engineering (Power Conversion), University of Pittsburgh, 2014 MS, Electrical Engineering, University of Pittsburgh, 2011 BS, Mechanical Engineering & Minor in Electrical Engineering, University of Pittsburgh, 2007 Executive Education Certificate, Tepper School of Business, Carnegie Mellon University, 2019 Research Focus Dr Grainger’s work lies at the intersection of power electronics, high-voltage engineering, and sustainable energy systems. He specializes in medium- and high-voltage power electronics (HVDC, STATCOM), resonant converters, and ultra-high-power-density designs leveraging SiC and GaN semiconductors. His investigations extend to electric-vehicle traction drives, solid-state transformers, optimized magnetics for aerospace applications, and resilient microgrids. He and his students routinely collaborate with NASA JPL, Johns Hopkins APL, Honeywell Aerospace, and the Naval Research Laboratory, leveraging Pitt’s NSF SHREC center to push the boundaries of power conversion in space and defense systems. Selected Research Themes High-frequency, high-density DC/DC converters for satellite power systems Radiation-tolerant GaN converters and point-of-load power stages Medium-voltage testbed development (13.8 kV, 5 MVA) Rare-earth-free permanent-magnet machine topologies Model-predictive control of multi-phase drives and microgrids Honors & Awards 2024 IEEE Region 2 Outstanding Educator Award 2024 Pitt STRIVE Outstanding DEI Service Award 2019 ESWP Engineer of the Year 2019 ASEE 2nd Place Best Paper Award 2019 SRI Undergraduate Best Mentor Award Richard K. Mellon Endowed Graduate Fellowship National Academies of Science & Engineering Ambassador Senior Member, IEEE Grants & Industry Partnerships Dr Grainger’s research has been continuously funded by federal agencies and industry partners including NASA JPL, Johns Hopkins APL, Honeywell Aerospace, the Naval Research Laboratory, Eaton, and the National Science Foundation through the SHREC Center. These awards support graduate students and post-docs working on next-generation power systems for aerospace, naval, and terrestrial applications. Laboratories & Teams Director, Electric Power Technologies Laboratory (EPTL) Associate Director, Energy GRID Institute Co-Director, Pitt AMPED (Advanced Multimodal Power and Energy Development) Faculty Affiliate, NSF SHREC Center
Thiago Batista Soeiro serves as a Full Professor with exceptional scholarly impact, evidenced by over 200 research publications and an h-index of 27. His work fundamentally advances power electronics applications in transportation and energy systems, particularly through innovations in electric vehicle infrastructure and sustainable power conversion technologies. Despite the absence of explicit institutional affiliation in source materials, his research permeates critical IEEE journals and conferences. Professor Soeiro's research portfolio centers on: Power converter design for electric vehicle charging systems AI-driven battery health estimation using electrochemical impedance spectroscopy Wireless power transfer optimization for automotive applications High-efficiency topologies for more electric aircraft Hydrogen energy system integration Advanced semiconductor utilization in grid-connected systems Analysis of his 2023-2025 publications reveals accelerating innovation in wide-voltage-range converters, predictive battery management, and fault-tolerant power systems. His work increasingly bridges machine learning with power electronics, notably through computation-light AI models for battery diagnostics, while maintaining strong focus on practical implementation challenges in EV charging and aircraft electrification. No scientific awards or honors were documented in the available materials. Similarly, information regarding student supervision, research grants, laboratory facilities, or collaborative teams was not provided in the source texts.
Zian Qin serves as an Associate Professor in the Department of Electrical Sustainable Energy at Delft University of Technology, Netherlands. His academic journey includes a B.Sc. from Beihang University (2009), M.Sc. from Beijing Institute of Technology (2012), and Ph.D. from Aalborg University (2015), all in Electrical Engineering, with a Visiting Scientist stint at RWTH Aachen University (2014). B.Sc., Electrical Engineering, Beihang University (2009) M.Sc., Electrical Engineering, Beijing Institute of Technology (2012) Ph.D., Electrical Engineering, Aalborg University (2015) His research centers on power electronics-based grid stability, solid-state transformers, and battery energy storage systems. Key contributions span DC microgrid control, magnetic material optimization, and EV charging infrastructure, with fingerprints highlighting expertise in power quality ( 100% ), voltage stability ( 87% ), and grid-forming applications ( 79% ). Current projects like ECS4DRES and GROW focus on resilient renewable energy systems and African energy storage solutions. His 154+ publications reveal strong emphasis on power electronics control ( 83% ), grid integration ( 79% ), and EV technologies ( 42% ), with recent work targeting microgrid vulnerability reduction and data-driven magnetic loss modeling. Awards include IEEE Prize Paper Awards (2023), World Top 2% Scientist recognition, and IEEE Innovation Awards (2024). IEEE International Challenge Excellent Innovation Award (2024) IEEE Open Journal Prize Paper Award (2023) World's Top 2% Scientist (2022-2024) Featured IES Journal Articles (2023) IEEE TIE Distinguished Reviewer (2020) As Founding Chair of IEEE Transportation Electrification Council Benelux Chapter and Dutch National for Cigre WG B4.101, he leads critical industry collaborations. His editorial roles in IEEE TPEL/TIE/JESTPE and projects like PROGRESSUS demonstrate significant grant leadership in next-generation power infrastructure. Lab activities focus on DC systems, energy conversion, and storage validation through Delft's Electrical Sustainable Energy facilities.
Lei Wu is a Professor and Anson Wood Burchard Chair Professor in the Department of Electrical and Computer Engineering at Stevens Institute of Technology. He holds a B.S. (2001) and M.S. (2004) in Electrical Engineering from Xi'an Jiaotong University, and a Ph.D. (2008) in Electrical Engineering from Illinois Institute of Technology. His research focuses on power system optimization, renewable energy integration, microgrid control, and cyber-physical systems resilience. Education: B.S. Electrical Engineering, Xi'an Jiaotong University (2001) M.S. Systems Engineering, Xi'an Jiaotong University (2004) Ph.D. Electrical Engineering, Illinois Institute of Technology (2008) Research Interests: Dr. Wu's work addresses challenges in power system operations, including optimization of renewable energy integration, electricity market design, and resilient microgrid control. He develops advanced algorithms for unit commitment, stochastic modeling of renewable resources, and cyber-physical security. His research emphasizes practical applications in grid resilience, demand response, and multi-energy system coordination. Awards: Fellow of IEEE (2022) NSF CAREER Award (2013) IBM Smarter Planet Faculty Innovation Award (2011) Grants & Professional Service: He leads grants on smart grid optimization, including projects from NSF, DOE, and industry partners. He serves as Editor for IEEE Transactions on Smart Grid and other journals, and has advised numerous students on energy-related research. His work on microgrid control and cyber-physical security has been widely recognized in industry and academia. Labs & Teams: Leads the Stevens Energy Systems Lab, focusing on advanced grid technologies and interdisciplinary collaborations between power systems, AI, and cybersecurity.
Rajesh Karki is a Professor in the Department of Electrical and Computer Engineering at the University of Saskatchewan’s College of Engineering. He holds a B.E., M.Sc., and Ph.D. in related fields. His research focuses on power system reliability, renewable energy integration, and microgrid resilience, with particular emphasis on addressing challenges posed by extreme weather, cyber threats, and decarbonization targets. Dr. Karki’s work spans theoretical modeling, probabilistic analysis, and practical implementation strategies for smart grids, energy storage systems, and distributed generation. His educational background includes advanced degrees in electrical engineering, complemented by professional engineering licensure (P.Eng.). His research has explored diverse topics such as wind energy curtailment mitigation, energy storage optimization, and demand response mechanisms in developing economies like Nepal. He has authored numerous peer-reviewed publications on grid resilience, reliability economics, and cyber-physical system security. Key themes in his work include: (1) quantifying the reliability value of energy storage in active distribution systems, (2) modeling cyber-physical threats to microgrids, and (3) developing frameworks for extreme weather-resilient infrastructure. Despite the volume of his publications (over 50 articles), no specific awards or grants are explicitly listed in the provided materials. His research often intersects technical, economic, and policy dimensions of sustainable energy systems.
Antonello Monti is a Professor and Director of the Institute for Automation of Complex Power Systems at RWTH Aachen University. His research focuses on modern power systems, including smart grid technologies, hybrid AC-DC grids, and quantum computing applications in energy systems. Recent publications demonstrate innovations in grid resilience, EV charging optimization, quantum-assisted power system planning, and advanced simulation techniques. His team develops open-source tools like JuliaGrid for power system analysis and validates concepts through real-time testing platforms. Research addresses energy transition challenges including renewable integration, grid modernization, cyber-physical security, and next-generation optimization methods combining quantum computing with traditional power engineering approaches.
Vinod M. Vokkarane is a Professor in the Department of Electrical and Computer Engineering at the University of Massachusetts Lowell, where he serves as Director of the Center for Smart Cyber-Physical Systems (SCyPS) and Director of Advanced Computer Network Labs. Previously, he was an Associate Professor at University of Massachusetts Dartmouth from 2004 to 2013 and a Visiting Scientist at MIT's Research Laboratory of Electronics from 2011 to 2014. His extensive research portfolio spans multiple domains of advanced networking and cyber-physical systems. Dr. Vokkarane earned his educational foundation with a B.S. from University of Mysore, India (1999), followed by an M.S. (2001) and Ph.D. (2004) in Computer Science from the University of Texas at Dallas. His dissertation focused on optical burst-switched networks, establishing the foundation for his future research trajectory. His research interests center on Cyber-Physical Systems, Network Optimization, Reliability, Smart Grids, and Cyber-Security, with particular expertise in the design, analysis, and modeling of architectures, protocols, and algorithms for ultra-high speed networks including Optical networks, Grid/Cloud networks, and Big-data networks. His work bridges theoretical foundations with practical implementations, often addressing critical challenges in network reliability, security, and efficiency. His research has received significant recognition through numerous best paper awards and substantial external funding. Analysis of his recent publications reveals a clear evolution toward increasingly sophisticated integration of cyber-physical systems with power infrastructure, particularly in the areas of grid resilience and observability. His work has expanded from fundamental optical networking research to address critical infrastructure challenges, with a growing emphasis on machine learning applications for network optimization and power system monitoring. The recent focus on PMU networks, disaster resilience, and cyber restoration demonstrates his strategic pivot toward addressing national security and critical infrastructure protection challenges. UMass Dartmouth Scholar of the Year Award (2011) UMass Dartmouth Chancellor's Innovation in Teaching Award (2010-11) University of Texas at Dallas Computer Science Dissertation of the Year Award (2003-04) Multiple Best Paper Awards including IEEE GLOBECOM 2005, IEEE ANTS 2010, ONDM 2015, ONDM 2016, and IEEE ANTS 2016 Texas Telecommunications Engineering Consortium Fellowship (2002-03) Dr. Vokkarane has successfully mentored numerous graduate students who have contributed significantly to his research projects, with several going on to successful careers in academia and industry. His research has been consistently supported by major funding agencies including NSF, DOE, and USMC, with recent projects totaling over $5 million in funding. Current projects include Unified Post-Disaster Restoration Planning for Cyber-Physical Power Distribution Systems (ONR, $550K), CyberCARE: Northeast University Cybersecurity Center (DOE, $3.5M), and Flexible Spectrum Allocation in Next-Generation Optical Networks (NSF, $350K). He leads the Center for Smart Cyber-Physical Systems (SCyPS) and Advanced Computer Network Labs at UMass Lowell, where his research teams work on cutting-edge problems in network architecture, cyber-physical security, and infrastructure resilience. His labs collaborate extensively with national laboratories and industry partners to translate theoretical advances into practical solutions for real-world infrastructure challenges.
Lei Lei is an Associate Professor at the University of Guelph, specializing in Computer Engineering. Her research focuses on Machine Learning/Deep Reinforcement Learning, Internet of Things (IoT)/Internet of Vehicles (IoV), Mobile Edge Computing, and Smart Grid Optimization. She explores cutting-edge applications in energy-efficient systems, autonomous vehicles, and intelligent transportation networks. Her work integrates advanced AI techniques with real-world challenges in communication and control systems. Key research areas include optimizing electric vehicle charging schedules using hierarchical deep reinforcement learning and enhancing vehicular networks through 6G communication protocols. She has pioneered methods for joint communication-control systems, securing federated learning models, and developing robust resource allocation strategies in IoT and edge computing environments. Lei Lei’s publications emphasize interdisciplinary solutions, bridging computer science, electrical engineering, and transportation systems. Her recent work addresses challenges in smart grid security, multitimescale control systems, and the application of AI tools like ChatGPT in connected vehicles. She is affiliated with the AI Affiliated Faculty at the University of Guelph, reflecting her contributions to artificial intelligence research.
Professor Chun-Hung Chen is a distinguished academic at George Mason University ’s Volgenau School of Engineering , where he holds the rank of Professor in the Department of Systems Engineering and Operations Research . He has also held professorships at National Taiwan University and visiting roles at institutions like University of Pennsylvania and Microsoft Research Asia . Education: PhD in Decision and Control, Harvard University (1994) MS in Electrical Engineering, National Taiwan University (1989) BS in Control Engineering, National Chiao-Tung University (1987) Research Interests focus on Stochastic Simulation Optimization , particularly his pioneering Optimal Computing Budget Allocation (OCBA) methodology. OCBA enhances simulation efficiency by dynamically allocating computational resources to critical design alternatives, reducing computation time by orders of magnitude. Applications span air transportation , healthcare , power grids , and semiconductor manufacturing . His 15 most recent articles (2022–2025) explore intersections of simulation optimization , artificial intelligence , reinforcement learning , and personalized medicine , emphasizing computational efficiency and stochastic systems in domains like microgrids and organ transplant logistics . Scientific Awards include: IEEE Fellow (2015) K.D. Tocher Medal (2017) Best Paper Awards at IEEE CASE (2019), LOGMS (2019), and IEEE ICC (2021) Harvard’s Eliahu I. Jury Award (1994) Advisory roles include editorial leadership in IIE Transactions , Journal of Simulation , and IEEE Transactions series. He has coordinated graduate programs at George Mason (2006–11, 2015–19) and led conferences like INFORMS International Meeting (2025) and Harvard Control Workshop (2024). His work is funded by organizations such as the National Science Foundation , National Institutes of Health , and Department of Energy , with applications in healthcare logistics and microgrid control .
Qing (Cindy) Chang is a Professor in the Department of Mechanical Engineering at the University of Virginia. Her research focuses on cyber-physical systems for smart manufacturing, real-time production control, and human-robot collaboration. Prior to academia, she worked at General Motors, earning three Boss Kettering Awards for innovation. She holds an M.S. from the University of Wisconsin-Madison and a Ph.D. in Manufacturing from the University of Michigan. Education: M.S. in Mechanical Engineering, University of Wisconsin - Madison Ph.D. in Manufacturing, University of Michigan – Ann Arbor Research Interests: Cyber-Physical Systems for Smart Manufacturing Real-time Production Control Knowledge-guided Machine Learning-based Control Human-Robot Collaboration in Industrial Settings Intelligent Maintenance and Energy Management Awards: 20 most influential professors in smart manufacturing (2020) NSF CAREER Award (2014) General Motors Boss Kettering Awards (2005, 2006, 2008) GM R&D Charles L. McCuen Special Achievement Awards (2005, 2006, 2008) Leadership & Grants: She serves on the board of NAMRI/SME and holds editorial roles in ASME, IEEE, and SME journals. Her work bridges AI, robotics, and manufacturing systems, with notable grants including the NSF CAREER Award. Labs & Teams: Her Intelligent Systems Lab develops AI-driven solutions for manufacturing efficiency and sustainability, focusing on energy management, predictive analytics, and human-robot collaboration.
