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Nanpeng YuView profile

Professor

• Smart Grid
• Power Systems
• Data-Driven Optimization
• +7 more

Dr. Nanpeng Yu is a Full Professor at the University of California, Riverside , serving as Vice Chair and Graduate Advisor in the Department of Electrical and Computer Engineering . He maintains cooperative faculty affiliations with the Department of Computer Science and Department of Statistics , and directs the Energy, Economics, and Environment Research Center at UCR. Education : B.S. in Electrical Engineering from Tsinghua University (2006), M.S. in Electrical Engineering and Economics, and Ph.D. from Iowa State University (2010) Prior Industry Experience : Senior Power System Planner and Project Manager at Southern California Edison (2011-2014) Dr. Yu’s research bridges smart grid technologies , data-driven optimization , and machine learning for energy systems. Key areas include voltage control , renewable energy integration , transportation electrification , and grid resilience . His recent work focuses on physics-informed graph learning for unit commitment problems and adversarial purification in power system classifiers. The AI-Energy Nexus Laboratory under Dr. Yu has produced impactful publications in Applied Energy , IEEE Transactions on Power Systems , and Transportation Research series, covering topics like heavy-duty EV charging infrastructure and dynamic distribution network reconfiguration . Lab members have won the American-Made Digitizing Utilities Grand Prize ($300,000) from the U.S. DOE. Leadership Roles : Chair, IEEE Power and Energy Society Distribution System Operation and Planning Subcommittee Chair, IEEE Power and Energy Society Working Group on Data-Driven Modeling for Power Distribution Networks Associate Editor, IEEE Transactions on Smart Grid and IEEE Power Engineering Letters Scientific Awards : Regents Faculty Fellowship Regents Faculty Development Award Multiple IEEE Best Paper Awards

Junjian QiView profile

Associate Professor

• Electric power systems
• Cascading failure
• Microgrid control
• +2 more

Junjian Qi serves as the Hohbach Endowed Associate Professor in the Department of Electrical Engineering and Computer Science at South Dakota State University's College of Engineering, holding this position since 2023. His academic journey includes prior appointments as Assistant Professor at Stevens Institute of Technology (2020-2023) and University of Central Florida (2017-2020), along with research roles at Argonne National Laboratory and University of Tennessee. His educational background includes: Ph.D. in electrical engineering from Tsinghua University, Beijing, China (2013) B.E. in electrical engineering from Shandong University, Jinan, China (2008) Dr. Qi's research centers on electric power systems resilience, with particular expertise in cascading failure mechanisms, microgrid control architectures, cyber-physical security vulnerabilities, and synchrophasor applications. His work integrates advanced data analytics and machine learning techniques to enhance grid stability against extreme weather events and cyber threats. Current investigations focus on developing distributed control strategies for inverter-dominated grids and modeling system interdependencies during failure propagation. Analysis of his 15 most recent publications (2021-2024) reveals a strong methodological shift toward data-driven approaches for power system challenges. Key trends include machine learning applications for cascading failure prediction, novel distributed control frameworks for AC/DC microgrids, and cybersecurity enhancements for inverter-based resources. His work consistently bridges theoretical models with real-world utility data, particularly evident in multiple Best Paper Award-winning publications analyzing actual outage sequences. Dr. Qi's scientific recognition includes: NSF CAREER Award (2020) Three consecutive Best Paper Awards at IEEE PES General Meetings (2022-2024) World's Top 2% Scientist designation in energy (2020-2023) IEEE PES Outstanding Working Group Award (2023) Multiple journal Best Paper Awards (IEEE Transactions on Power Systems, Journal of Modern Power Systems) He currently leads significant research initiatives including an NSF CAREER project ($500k) on cascading failure analysis and an NSF collaborative grant ($219k) for grid stability, alongside previous DOE funding ($1.8M) for cybersecurity of distributed energy resources. His service includes editorial roles for IEEE Transactions on Power Systems and IEEE Power Engineering Letters, plus leadership in IEEE PES technical committees focused on voltage control and smart grid security.

Di ShiView profile

Associate Professor

• Power System Data Analytics
• Energy Storage Systems
• Artificial Intelligence
• +3 more

Di Shi is an Associate Professor at the Klipsch School of Electrical and Computer Engineering , New Mexico State University (NMSU), holding the Paul W. and Valerie Klipsch Distinguished Professorship. He previously founded the AI energy startup AInergy, LLC and held leadership roles at GEIRI North America, NEC Laboratories America, and Arizona State University. Education: PhD in Electrical Engineering, Arizona State University (2012) MS in Electrical Engineering, Arizona State University (2009) BS in Electrical Engineering, Xi'an Jiaotong University (2007) His research focuses on power system data analytics , energy storage , artificial intelligence , and IoT applications for grid stability and renewable integration. His work bridges theoretical innovation with real-world deployment, including software adopted by 15 utility companies. Recent publications highlight his leadership in deep reinforcement learning for grid control, blockchain frameworks for energy management, and tensor decomposition for efficient load modeling. He has secured a $6M NSF grant for AI-driven digital twinning to address climate-aware energy resilience. Awards & Recognition: 2025 Paul W. and Valerie Klipsch Distinguished Professorship 2024 University Research Council Mid-Career Award 2024 IET Fellow Multiple IEEE Best Paper Awards (2019–2022) 2019 L2RPN AI Competition Championship He serves as an editor for IEEE Transactions on Power Systems , IET Generation, Transmission & Distribution , and other journals, and leads the IEEE Task Force on IoT for Power Systems . His team’s patents cover AI-driven load modeling , energy storage scheduling , and state estimation , with 42 granted or pending.

Roozbeh TorkzadehView profile

Researcher

• Smart Grids
• Synchrophasor Technologies
• Power Quality
• +3 more

Roozbeh Torkzadeh is a researcher with expertise in smart grids, synchrophasor technologies, and power quality. He completed his M.Sc. (Hon.) in Electrical Engineering at Yazd University (2013) and earned his Ph.D. from the Department of Electrical Engineering at Eindhoven University of Technology (TU/e) in 2023. His Ph.D. project was funded by Netbeheer Nederland. He has held research roles at Universidad Loyola Andalucía (Spain) and TenneT TSO BV (Netherlands), and is currently a guest researcher at TU/e while working as a Senior Electrical Engineer at Shell Global Solutions International, focusing on grid connection, renewable integration, and decarbonization. Education: M.Sc. (Hon.) in Electrical Engineering, Yazd University (2013) Ph.D. in Electrical Engineering, Eindhoven University of Technology (2023) Roozbeh’s research spans power systems, renewable energy integration, and grid stability. He has contributed to voltage dip assessment, energy transition impacts on network quality, and PMU placement optimization. His work emphasizes practical challenges in wide-area measurement systems, fault current injection, and synthetic inertia control for low-inertia grids. Recent publications highlight trends in energy transition-driven grid modifications, voltage dip analysis, and synchrophasor applications. Key subfields include network modeling, renewable energy markets, and hydrogen scheduling. Scientific Awards: Next Generation Network (NGN) Showcase Presentation Award (CIGRE, 2021) His Ph.D. grant from Netbeheer Nederland and collaborations with Dutch grid operators underscore his industry-academia engagement. Current roles in Shell and TU/e reflect his focus on electrification and decarbonization projects.

• Data Analytics
• Artificial Intelligence Applications in Power Systems
• Renewable Energy Integration
• +3 more

Anamitra Pal is an Associate Professor at Arizona State University's School of Electrical, Computer and Energy Engineering. His work focuses on power system resilience, renewable energy integration, and time-synchronized measurement analytics. He leads research initiatives combining artificial intelligence with grid modernization challenges. Ph.D. Electrical Engineering, Virginia Tech (2014) M.S. Electrical Engineering, Virginia Tech (2012) B.E. Electrical and Electronics Engineering, Birla Institute of Technology (2008) Prior to ASU, Pal conducted postdoctoral research at Virginia Tech's Network Dynamics and Simulation Science Laboratory (2014-2016). His research interests center on enhancing grid stability through: Advanced synchrophasor data analytics AI-driven power system security frameworks Renewable generation integration strategies Critical infrastructure protection during extreme events Recent publications demonstrate his focus on grid resilience during wildfires, deep learning-based state estimation, and innovative PMU applications. Pal has received multiple accolades including the NSF CAREER Award (2022) and IEEE Phoenix Section's Outstanding Young Professional Award (2019).

• Power System Control
• Smart Grids
• Communication Systems
• +11 more

Lars Nordström is a Professor at the Division of Electric Power and Energy Systems within KTH Royal Institute of Technology, Stockholm, Sweden. His work bridges control systems , communication networks , and power systems , with a focus on future architectures, functionality, and quality aspects of ICT for power grid operations. He has led initiatives such as the Swedish Centre of Electric Power Engineering and served as Thematic Leader for Smartgrids in KIC InnoEnergy. In 2014, he was a Visiting Professor at Washington State University. Education : Ph.D., MSc.EE Nordström's research explores the intersection of smart grids , machine learning , and cybersecurity for power systems. Key areas include: Wide-Area Monitoring and Control (WAMC) systems Decentralized control strategies for DC microgrids Impedance modeling using neural networks Data-driven methods for islanding detection ICT reliability and protocol design for grid operations His recent publications emphasize machine learning applications in power systems, including LSTM networks for EV charging management, graph attention networks for stability monitoring, and digital twin approaches for cyber-attack mitigation. These works span disciplines such as Smart Grids, Power Electronics, and Data Science. Scientific Recognitions : Senior Member, IEEE Senior Member, CIRED Senior Member, Cigre Past Chairman, Swedish IEC TC57 Mirror Committee Nordström actively teaches and examines graduate courses like Communication and Control in Electric Power Systems and Computer Applications and Machine Learning in Electric Power Systems . His work influences industry practices through collaborations on digital substations, energy market analysis, and resilience strategies.

Ryan KoView profile

Professor

• Cyber Security
• Data Provenance
• Industrial Control Systems (ICS) Security
• +6 more

Professor Ryan Ko is a leading academic in Cyber Security at the University of Queensland (UQ), serving as Chair and Director of the UQ Cyber Research Centre, Director of Research at the School of Electrical Engineering and Computer Science, and a member of UQ's Academic Board. He holds a BEng (Computer Engineering) and PhD from Nanyang Technological University, Singapore. His research focuses on data provenance, industrial control systems (ICS) security, privacy-preserving technologies, and AI-driven cybersecurity solutions. Ko has pioneered initiatives such as the UQ Cyber Centre, interdisciplinary cybersecurity education programs (MCyber, PGDipCyber), and the Oceania Cybersecurity Challenge. He has attracted over AUD 20 million in competitive grants as lead investigator, including the NZ$12.2M STRATUS project. Ko’s work spans industry and policy, including advisory roles with INTERPOL, governments, and NGOs. He has authored over 100 publications, contributed to ISO standards (e.g., ISO/IEC 21878), and co-founded cybersecurity startups. Awards include Fellowships from the Australian Computer Society and Queensland Academy of Arts and Sciences, and the CSA Ron Knode Service Award. Education: Bachelor of Engineering (Computer Engineering) (Hons.), Nanyang Technological University (2005) PhD in Computer Science, Nanyang Technological University (2011) Awards: Fellow, Australian Computer Society (2016) Fellow, Queensland Academy of Arts and Sciences (2020) Young Professional Award, Singapore Government (2018) Grants & Leadership: AUD 20M+ lead investigator grants; NZ$12.2M STRATUS project (2014–2018) Established UQ Cyber Centre (2019) and NZ’s first cybersecurity graduate program (2012) His research emphasizes returning data control to users, with applications in agriculture, energy, and critical infrastructure. Ko’s contributions include patents, open-source tools (e.g., Kali Linux), and frameworks like TrustCloud for cloud accountability.

Liz RatnamView profile

Associate Professor

• Control of Power Systems
• Optimization of Energy Systems
• Secure and Resilient Power Grids
• +3 more

Associate Professor Liz Ratnam is a leading academic in the Department of Electrical and Computer Systems Engineering at Monash University, serving as Deputy Postgraduate Director of Education ECSE. Her expertise spans power systems control, energy optimization, and resilient grid design. She holds a BEng (Hons I) and PhD in Electrical Engineering from the University of Newcastle (2006 and 2016), with postdoctoral research at UC San Diego and Berkeley. She previously served as Senior Lecturer and Sub-Dean for Educational Programs at ANU's College of Engineering & Computer Science, supported by a Future Engineering Research Leader (FERL) Fellowship. Her current research focuses on advancing transactive energy markets, EV coordination in distribution networks, and secure grid operations. She leads major grants including the National Facility for Electricity Grid Security (ARC LIEF 2023) and projects on EV fast-charging infrastructure. Education Background: - BEng (Hons I) in Electrical Engineering, University of Newcastle (2006) - PhD in Electrical Engineering, University of Newcastle (2016) Research Interests: Resilient, carbon-neutral power grid design Control and optimization of energy systems Synchrophasor-based estimation for grid stability Transactive multi-agent systems for energy markets Electric vehicle integration and coordination in unbalanced grids Grants & Projects: ARC Linkage Infrastructure Grant LE23010058 (2023): National Facility for Electricity Grid Security ARC Discovery Project DP22010135 (2022): Neural Architecture Search for Deep Learning ARC Linkage Project LP21200473 (2022): Building Australia's EV Fast-Charging Infrastructure Awards & Memberships: Fellow of Engineers Australia Senior Member of IEEE FERL Fellowship (ANU)

Filippo MalandraView profile

Assistant Professor

• Internet of Things
• Wireless Communications
• 5G/4G Cellular Networks
• +4 more

Filippo Malandra is an Assistant Professor in the Department of Electrical Engineering at the University at Buffalo, part of the School of Engineering and Applied Sciences. His research focuses on Internet of Things (IoT), wireless communications, 5G/4G cellular networks, network performance analysis, smart grid communications, optimization, and machine learning applications. PhD in Electrical Engineering from École Polytechnique de Montréal Master of Engineering in Telecommunications Engineering from Politecnico di Milano Bachelor of Engineering in Telecommunications Engineering from Politecnico di Milano His research interests include experimental testbed development for 5G-enabled smart grids, analytical modeling of cellular network delays, and machine learning frameworks for optimizing network performance under environmental factors. He has contributed to tools like WTTool for 5G network simulation and PeRF-Mesh for RF-mesh network analysis. Recent work emphasizes 5G testbed experimentation (e.g., ExTODS), weather-based signal prediction, and CBRS spectrum analysis. He has explored synergies between federated learning and O-RAN architectures for elastic network services. Active service roles include TPC Member for IEEE SECON 2019 and reviewer for IEEE journals and conferences like DRCN. Recipient of NSF CRII grant (2021) for CNS research on IoT-aware dynamic spectrum sharing. Collaborates on projects like UBSpot (aerial-ground wireless networks) and smartDESC (distributed energy storage control).

Ravikumar BhimasinguView profile

Professor

• Computer-aided power system analysis
• Renewable energy integration
• AI applications in power systems
• +5 more

Ravikumar Bhimasingu is a Professor at the Indian Institute of Technology Hyderabad , Department of Electrical Engineering. His work focuses on advanced power system analysis and control strategies for renewable energy integration. Research Interests : Computer-aided power system analysis, AI applications for power systems, microgrid control, power electronics, renewable energy integration Lab : Leads research activities in power systems and renewable energy Scientific Contributions : With over 72 publications, his recent work explores: Grid-forming inverters and predictive control techniques Fault location algorithms using synchrophasor data Virtual inertia and transient stability improvements Advanced EV charging systems with power quality enhancements

Lamine M. MiliView profile

Professor

• Power Systems
• Signal Processing
• Robust Estimation Theory
• +7 more

Lamine M. Mili is a Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His expertise spans power systems, signal processing, and robust estimation theory. He holds an IEEE Fellowship (2016) for contributions to robust state estimation in power systems. Mili's research focuses on advancing methodologies for power system reliability, control, and integration of renewable energy sources. His work includes studies on dynamic state estimation, nonlinear dynamics, bifurcation theory, and quantum computing applications. He has contributed extensively to resilience engineering and computational social science in power systems. Mili’s recent articles address challenges in smart grids, quantum circuit error prediction, and multifractal signal analysis in EEG. His research often combines advanced statistical techniques with real-world grid data, emphasizing robustness and adaptability in dynamic environments. Education: Ph.D., University of Liège, 1987 M.S., University of Tunis, 1983 B.S., Swiss Federal Institute of Technology, Lausanne, 1976 Research Interests: Power system stability and control State estimation and robust filtering Quantum computing for power systems Resilience and cyber-physical-social systems Nonlinear dynamics and bifurcation analysis His recent publications reflect a focus on hybrid power systems, probabilistic methods, and data-driven approaches for grid optimization. The 2025 articles highlight advancements in photovoltaic state estimation, quantum error prediction, and robust modulation techniques. Mili’s work often bridges theoretical models with practical grid applications, emphasizing uncertainty quantification and real-time monitoring.

Gareth TaylorView profile

Professor

• Power Systems
• Smart Grids
• Renewable Energy Systems
• +7 more

Professor Gareth Taylor is a Professor of Power Systems and Director of the Brunel Interdisciplinary Power Systems (BIPS) Research Centre at Brunel University London's College of Engineering, Design and Physical Sciences. He serves as Module Leader for the MSc Sustainable Electrical Power program and has been actively involved with the university since May 2000, progressing from National Grid Post-doctoral Scholar to his current position as Professor (appointed in 2012). He previously served as Head of the Department of Electronic and Electrical Engineering from May 2019 to June 2023 and holds a Visiting Professor position at Imperial College London (2023-2026). Professor Taylor earned his BSc in Applied Physics from Royal Holloway College, University of London (1987), followed by an MSc in Scientific and Engineering Software Technology from the University of Greenwich (1992), and completed his PhD in Computational Solid Mechanics at the University of Greenwich in March 1997. His doctoral research focused on finite volume methods for material non-linearity within multi-physics frameworks. His research spans power systems engineering with particular emphasis on smart grid technologies, renewable energy integration, and advanced computational methods. Professor Taylor has contributed to over 250 research publications in areas including power system operation and management, reactive power control, voltage regulation, and high-performance computing applications in electrical power systems. His work addresses critical challenges in modern power systems, particularly those related to the integration of renewable energy sources and the development of more resilient grid infrastructure. Analysis of his recent publications reveals a strong focus on addressing contemporary power system challenges, particularly the integration of renewable energy sources, smart grid technologies, and advanced computational methods. His work spans from fundamental power system analysis to practical applications in grid operation, with increasing emphasis on cybersecurity aspects of power system monitoring and the challenges posed by reduced system inertia in grids with high renewable penetration. Senior Member of IEEE Fellow of the Institute of Engineering and Technology (FIET) Chartered Engineer Fellow of the Higher Education Academy (FHEA) UK Regular Member for CIGRE Study Committee D2 (2016-2022) Member of Strategic Advisory Group for CIGRE Study Committee D2 (2023) Professor Taylor has led numerous significant research projects including TDX-ASSIST (€5.2M), e-HIGHWAY2050 (€8.2M), and HiPerDNO (€5.4M), with funding from EPSRC, European Commission, National Grid, and other major organizations. His current research portfolio includes projects on novel decoupled active/reactive power oscillation response, digitalization of power systems operation, and examining net zero policy in European energy markets. He also directs the BIPS Research Centre, which focuses on interdisciplinary power systems research with strong industry connections.

• Power Systems
• Smart Grids
• Synchronized Measurement Technology
• +6 more

Vladimir V. Terzija is a prominent researcher specializing in power systems engineering with a focus on smart grid technologies, synchronized measurement systems, and power system protection. His extensive publication record spans over two decades, demonstrating continuous contributions to the field of electrical power engineering across numerous IEEE journals and conferences. Terzija's research primarily centers on advanced power system monitoring, protection, and control methodologies. His work has significantly contributed to the development of synchronized measurement technology applications, fault analysis algorithms, and state estimation techniques for modern power systems. He has pioneered approaches for wide-area monitoring systems, transmission line fault analysis, and integrating renewable energy resources into power grids while maintaining stability and reliability. His research spans from fundamental power system theory to practical implementations addressing contemporary challenges in grid operation. Analysis of his recent publications reveals a strong focus on integrating artificial intelligence and machine learning techniques into power system applications, particularly for condition monitoring, anomaly detection, and predictive maintenance. His work increasingly addresses challenges posed by the energy transition, including grid stability with high renewable penetration, multi-energy system integration, and advanced control strategies for low-inertia power systems. The interdisciplinary nature of his research connects power engineering with data science, optimization theory, and cybersecurity. Throughout his career, Terzija has collaborated extensively with researchers across Europe and internationally, as evidenced by his numerous co-authored publications with institutions worldwide. His work appears consistently in top-tier IEEE publications, indicating recognition by the power engineering community. While specific awards aren't documented in the available publication records, his sustained research productivity and influence in the field suggest significant professional recognition. Terzija has supervised numerous research projects focused on power system monitoring and control, with particular emphasis on practical implementations that bridge theoretical developments with real-world grid applications. His work on WAMS (Wide Area Monitoring Systems), fault location algorithms, and state estimation techniques has contributed to advancing grid operational capabilities. The research trajectory shows increasing focus on addressing challenges associated with renewable energy integration, grid digitalization, and maintaining stability in modern power systems. His research group appears to focus on developing advanced monitoring and control systems for power networks, with particular expertise in synchrophasor technology applications. The collaborative nature of his work suggests involvement in international research consortia addressing contemporary power system challenges, particularly those related to grid stability in systems with high renewable penetration and the development of intelligent monitoring solutions for power infrastructure.

• Power Systems
• Power System Restructuring
• FACTS Technology
• +8 more

Sri Niwas Singh serves as Chair Professor in the Department of Electrical Engineering at the Indian Institute of Technology, Kanpur, where he has established himself as a leading expert in power systems engineering with significant research contributions spanning multiple critical areas. His educational qualifications include: PhD in Electrical Engineering from IIT Kanpur (1995) M.Tech in Electrical Engineering from IIT Kanpur (1989) B.Tech in Electrical Engineering from KNIT Sultanpur (1987) Professor Singh's research program focuses on Power System Restructuring, FACTS Technology, Optimal Power Dispatch and Security Analysis, Power System Dynamics, Operation and Control, Distribution System Planning and Demand Side Management, and Application of Genetic Algorithms and Artificial Neural Networks in Power Systems. His work bridges theoretical concepts with practical applications, particularly in smart grid technologies and renewable energy integration. His publication record reveals a consistent research trajectory addressing evolving power system challenges, with increasing emphasis on renewable energy integration and computational intelligence techniques. The progression from traditional power system analysis toward smart grid technologies and AI applications demonstrates his ability to adapt research focus to emerging industry needs. His significant professional recognitions include: 2013 IEEE Educational Activities Board Meritorious Achievement Award in Continuing Education Three PhD theses supervised by him receiving the POSOCO Power System Award (2012) Humboldt Research Fellowship (awarded 2005 and 2007) INAE Young Engineer Award (2000) C.B.I.P. Young Engineer Award (1996) Professor Singh has mentored numerous graduate students, with three of his PhD students receiving the prestigious POSOCO Power System Award in 2012. His research has attracted substantial funding and collaboration opportunities, supporting advanced work in power systems analysis and control. His laboratory focuses on power system simulation, renewable energy integration studies, and smart grid technology development, with a research team comprising PhD scholars and industry collaborators working on cutting-edge power engineering problems.

• Electrical Engineering
• Power Systems
• Smart Grids
• +4 more

Daniel Baltensperger is a Postdoctoral Fellow at NTNU affiliated with the Department of Electric Energy and Department of Language and Literature . His academic rank is classified as Research Fellow . Research Focus: Specializing in power systems and grid stability, Baltensperger's work explores hardware-in-the-loop simulation, dynamic state estimation, system protection schemes, and under-frequency load shedding. His research emphasizes adaptive algorithms for critical contingency management and real-time validation of smart grid technologies. Publications Trends: Recent works (2021–2023) focus on power system resilience, synchrophasor integration, and predictive control strategies. Collaborative efforts include co-authoring with Santiago Sanchez Acevedo, Salvatore D'Arco, and Kjetil Uhlen. Contact: Email: daniel.s.baltensperger@ntnu.no . Address: Elektro E/F, Gløshaugen, NTNU.