Prof. Ramakrishna Gokaraju is a Professor and Graduate Chair in the Department of Electrical and Computer Engineering at the University of Saskatchewan. His academic journey includes roles as Assistant Professor (2003), Associate Professor (2009), and full Professor (2015). He holds a B.E. from NIT Trichy (1992), M.Sc. and Ph.D. from the University of Calgary (1996, 2000). His research focuses on power system protection, smart grids, and sustainable energy systems, including small modular reactors (SMRs) and renewable integration. He has advised 8 PhD and 25+ Master’s students, with over 80 publications in top journals/conferences. Dr. Gokaraju’s honors include the Izaak Walton Killam Memorial Scholarship (1998–2000) and the Professor of the Year Award (2008). He has held visiting roles at the University of Manitoba (2009–2010), IIT Kanpur (2018), and institutions in Australia and India. His work emphasizes high-speed digital relaying, PMU-based solutions, and transient stability protection. Current research includes wind generator modeling, SMR integration, and energy storage systems for remote communities. His technical contributions span fault location algorithms, grid resilience enhancement, and GPU-based optimization for transport systems. Ongoing projects explore hybrid energy systems combining SMRs with renewables. Lab affiliations include the Power Systems Research Group at the University of Saskatchewan, focusing on smart grid innovation and sustainable energy solutions.
Larry Pileggi is the Coraluppi Head and Tanoto Professor of Electrical and Computer Engineering at Carnegie Mellon University (CMU). He is also the Department Head of CMU’s ECE Department and has held prior roles at Westinghouse Research and Development and the University of Texas at Austin. His work bridges academic research and industry innovation, with co-founding ventures like Fabbrix Inc., Extreme DA, and Pearl Street Technologies. Dr. Pileggi earned his Ph.D. in Electrical and Computer Engineering from CMU (1989), following an M.S. (1984) and B.S. (1983) in Electrical Engineering from the University of Pittsburgh. His research focuses on three core areas: secure integrated circuit hardware (mitigating supply-chain threats), integrated circuits design methodologies (supporting sub-20nm CMOS and heterogeneous technologies), and power systems simulation (developing robust grid analysis tools like SUGAR). He has been recognized with numerous awards, including the prestigious 2023 Phil Kaufman Award for contributions to electronic system design, and is an IEEE Fellow. His academic leadership includes fostering maker initiatives and interdisciplinary research programs to address future challenges in energy and computing systems. Pileggi’s advising record includes over 47 Ph.D. students, many of whom collaborate with him in industry ventures. Current and past grants support his work on resilient power grids and novel memory technologies, reflecting a commitment to both theoretical and applied research. His lab, the Pileggi Lab, develops cutting-edge solutions for energy and integrated systems, emphasizing scalable simulation, secure hardware design, and next-generation memory architectures. Collaborations span institutions like ETH Zurich and industry partners in EDA and semiconductor sectors.
Ram Rajagopal is an Associate Professor of Civil and Environmental Engineering and Electrical Engineering at Stanford University, and a Senior Fellow at the Precourt Institute for Energy. He leads the Stanford Sustainable Systems Lab (S3L), focusing on large-scale monitoring, data analytics, and stochastic control for infrastructure networks, particularly power systems. His research emphasizes renewable energy integration, smart distribution systems, and demand-side data analytics. Education: PhD in Electrical Engineering and Computer Sciences & MA in Statistics (UC Berkeley), MS in Electrical and Computer Engineering (UT Austin), and BEng in Electrical Engineering (Federal University of Rio de Janeiro). Research interests include power grid optimization, renewable energy systems, and data-driven approaches to infrastructure challenges. He has pioneered work in grid flexibility, distributed energy resources, and machine learning applications for energy systems. His lab develops technologies like Smart Dim Fuses and the EV-EcoSim platform for EV charging infrastructure optimization. Received NSF CAREER Award, Powell Foundation Fellowship, and Berkeley Regents Fellowship Over 30 patents and best paper awards Advises/founded companies in sensor networks, power systems, and data analytics Labs/Teams: Stanford Sustainable Systems Lab (S3L), Powernet Project. His work spans grid resilience, energy equity, and scalable energy solutions.
Dr. K. Max Zhang is a Professor in the Sibley School of Mechanical and Aerospace Engineering at Cornell University. He is the director of the Energy and the Environment Research Laboratory (EERL) and a fellow at the Atkinson Center for a Sustainable Future. His research is deeply interdisciplinary, focusing on sustainable energy systems, air quality, and environmental justice, with significant impacts on policy and community development in New York and beyond. Ph.D., Mechanical Engineering, University of California-Davis, 2004 B.S., Thermal Engineering, Tianjin University, 1998 B.A., English Language, Tianjin University, 1998 Dr. Zhang’s research centers on the integration of energy and environmental systems. He investigates air pollution dynamics using advanced numerical models like CTAG, with applications in near-source pollution, indoor air quality, and environmental justice. His work on renewable energy systems includes designing sustainable solar farms and managing distributed energy resources such as heat pumps to enhance grid flexibility. He also leads a pioneering initiative to create the first statewide public IoT network in the U.S., enabling hyperlocal weather forecasting and microclimate monitoring. His recent publications reflect a strong trend toward agrivoltaics, peer-to-peer energy markets, and IoT-based environmental monitoring. These works demonstrate a consistent focus on data-driven modeling, community-scale energy solutions, and the integration of social considerations into technical systems. The keywords across his articles highlight expertise in sustainability, machine learning, air quality, and energy transition. Cornell Town-Gown Achievement Award (2022) Engaged Scholar Prize, Cornell University (2017) People's Choice Sign of Sustainability Award, Sustainable Tompkins (2016) Scientific and Technological Achievement Award, Environmental Protection Agency (2015) Fellow of the American Society of Mechanical Engineers Dr. Zhang is actively involved in mentoring students and securing research grants from agencies such as the National Science Foundation (NSF) and the New York State Energy Research and Development Authority (NYSERDA). His projects often involve interdisciplinary collaboration across eight Cornell colleges and 16 academic departments. He has led initiatives such as the Cornell Atkinson Academic Venture Fund projects and the development of a county-level energy roadmap for Tompkins County. He also teaches courses in engineering thermodynamics, future energy systems, and air quality, emphasizing experiential and community-based learning. Dr. Zhang leads the Energy and the Environment Research Laboratory (EERL) and collaborates with the Atkinson Center for a Sustainable Future. His lab functions as a hub for innovation in sustainable communities, combining advanced modeling with real-world applications. Through partnerships with community organizations, government agencies, and industry, his team develops science-driven solutions to urban and rural sustainability challenges.
Mohsen Ghafouri is an Associate Professor at the Concordia Institute for Information Systems Engineering (Concordia University). His research focuses on cybersecurity, smart grids, and cyber-physical systems with emphasis on securing energy infrastructure against cyber-attacks. Key areas include detection and mitigation of false data injection attacks, grid resilience against load-altering threats, and secure transactive energy markets. Research interests include wide-area monitoring systems (WAMS), microgrid control, and integration of renewable energy sources. He has developed frameworks for real-time anomaly detection in power systems, blockchain-based security solutions, and machine learning approaches for cyber threat identification. His work addresses vulnerabilities in smart grid components like IEC 61850 substations and EV ecosystems. Recent publications (2024-2025) highlight advancements in securing FACTS controllers, EV charging systems, and distributed energy resources. He has proposed novel mitigation strategies using reinforcement learning, graph neural networks, and federated learning. No scientific awards or grant details are provided in the source text. No advising relationships or lab affiliations are explicitly stated.
Amr Youssef is a Professor at the Concordia Institute for Information Systems Engineering, Concordia University. His research focuses on applied cryptography, network security, cyber-physical systems security, blockchain, and privacy. He has contributed extensively to securing smart grids, IoT devices, and web applications through cryptographic protocols and machine learning-driven solutions. His work addresses critical challenges in cybersecurity, including e-voting systems, fault-tolerant differential protection, and privacy-preserving communication protocols. He explores vulnerabilities in modern systems such as SSO permissions, JavaScript exploits, and stalkerware tools, while developing frameworks like MEGR-APT for APT detection and TEE-Receipt for non-repudiation. Youssef’s research integrates interdisciplinary approaches, combining cryptography with AI (e.g., vision transformers for power quality analysis) and leveraging trusted execution environments (TEE) for secure computing. His projects often involve collaboration with industrial standards (e.g., IEC 61850), emphasizing practical implementations in real-world systems.
Sascha van Schendel is an Assistant Professor in Data Protection & Cybersecurity at the Department of Law & Markets, Erasmus School of Law, Erasmus University Rotterdam. She is affiliated with the Erasmus Centre of Law and Digitalization and contributes to the Sectorplan SSH-Breed research initiative on the influence of digitalization on work, prosperity, and entrepreneurship. Her research lies at the intersection of law, technology, and fundamental rights, with a focus on data protection, privacy, algorithmic governance, and the regulation of emerging technologies in public and environmental domains. She has published widely on topics including GDPR compliance, privacy by design, smart energy systems, AI in criminal justice, and the legal implications of predictive policing. The recent publications reflect a strong trend toward the regulation of data in public infrastructure (e.g., energy grids), algorithmic accountability in law enforcement, and the integration of legal and technical perspectives in privacy-preserving systems. Her work spans environmental law, criminal procedure, and digital constitutionalism, demonstrating interdisciplinary reach. Scientific Awards: No awards explicitly mentioned in the provided text. Advising and Grants: While no formal PhD or Master’s students are listed, Dr. van Schendel has been involved in significant research projects such as the NWO-funded Megamind project on smart energy grids, indicating experience with competitive grant funding. She actively collaborates with legal scholars and contributes to public policy debates, including responses to national legislation like the Dutch Cybersecurity Bill. Labs and Teams: She is a core member of the Erasmus Centre of Law and Digitalization, a research hub focusing on the legal challenges of digital transformation. Her work is embedded in interdisciplinary collaborations involving law, technology, and public policy experts.
Professor Ernest Foo is a distinguished academic at Griffith University's School of Information and Communication Technology, specializing in cybersecurity with a focus on industrial control systems and cryptographic protocols. With over 15 years of experience in computer networking, he has established himself as a leading expert in SCADA security and smart grid cybersecurity. His research has significant practical applications in critical infrastructure protection, and he has developed hands-on security training programs that have trained professionals from major Australian utilities and government agencies. Professor Foo's educational background includes: Bachelor of Engineering with Honours in Electronic and Computer Engineering from University of Queensland Doctor of Philosophy from Queensland University of Technology Professor Foo's research interests center around secure cryptographic protocols with specific applications in industrial control system security and cyber physical systems. His work spans SCADA security, smart grid protection, wireless sensor network security, and post-quantum cryptography. He has made significant contributions to understanding vulnerabilities in industrial protocols like Modbus and DNP3, and has pioneered the application of process mining and data mining techniques for attack detection in critical infrastructure systems. His research bridges theoretical security concepts with practical implementations in real-world industrial environments. Professor Foo's recent publications demonstrate a clear trajectory toward increasingly sophisticated security frameworks for critical infrastructure. His work shows a progression from foundational SCADA security research to advanced applications of artificial intelligence, machine learning, and formal methods in cybersecurity. A notable trend is the integration of zero trust principles with industrial control systems, alongside growing emphasis on post-quantum cryptographic solutions. His publications span high-impact journals and conferences in cybersecurity, with increasing focus on anomaly detection in cyber-physical systems and the application of graph-based machine learning techniques to network security challenges. Professor Foo's notable scientific achievements include: Best paper award at the 2nd International Cyber Resilience Conference for "Gap analysis of Intrusion Detection in Smart Grids" Professor Foo has secured significant research funding including an ARC Linkage grant with Powerlink Queensland focused on cyber security for electricity sub-stations. He currently leads multiple research projects including Westpac Micro-Credentials in Financial Crime Investigation, Digital Banking Micro-credentials with ANZ, and research on quantum-safe cryptography. As a dedicated educator, he serves as Program Director for multiple cybersecurity programs including the Master of Cyber Security, and has supervised numerous doctoral and masters students. His Cyber Security: Industrial Control System course, conducted annually from 2013-2018, featured innovative hands-on training with real-world participants from major Australian utilities. Professor Foo has been instrumental in establishing the SCADA security research laboratory with multiple vendor system miniatures running industrial PLCs. His work bridges theoretical security concepts with practical implementations, making significant contributions to the security of industrial control systems and critical infrastructure worldwide.
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.
Yuvraj Agarwal is a Professor in the School of Computer Science at Carnegie Mellon University , where he leads the SYNERGY Labs . His research focuses on Systems and Networking with emphasis on Embedded Systems , Security , and Energy Efficiency in computing environments. He has been recognized with the NSF Expeditions in Computing Award for Computational Decarbonization research and multiple best paper awards. Education : PhD in Computer Science from University of California, San Diego Research Leadership : Founder/Director of SYNERGY Labs; Executive Director of NSF Expeditions in Variability (2010-2013) Research Trajectory : Recent publications highlight his work on Privacy-preserving smart classroom systems (EduSense, ClassID) IoT security labeling frameworks Audio privacy protection mechanisms Computational decarbonization of infrastructure His research combines hardware-software co-design with societal impact considerations. Scientific Recognition : NSF Expeditions in Computing Award for CoDec (2024) Ubicomp/IMWUT Distinguished Paper Award (2024) CHI Best Paper Honorable Mention (2022) Advising & Collaboration : Mentors students in IoT systems , privacy research , and green computing . Collaborates with institutions including University of Massachusetts Amherst and industry partners like Johnson Controls. Grants include NSF funding for multi-university research initiatives.
Wei Sun is an Associate Professor in the Department of Electrical and Computer Engineering at the University of Central Florida, where he also serves as the Director of the Siemens Digital Grid Lab. His research focuses on power system restoration, self-healing smart grids, cyber-physical security, and renewable energy integration. Dr. Sun received his Ph.D. from Iowa State University in 2011, and his M.S. and B.S. from Tianjin University in 2007 and 2004, respectively. Prior to joining UCF, he was an Assistant Professor at South Dakota State University (2013-2015), a power system engineer at Alstom Grid (2011-2012), a visiting scholar at the University of Hong Kong (2011), and an intern at California Independent System Operator (2010). His research interests include: Power System Restoration and Self-healing Smart Grid Resilient and Secure Critical Infrastructure Cyber-Physical Systems Renewable Energy and Microgrid Distributed Energy Resources Integration Dr. Sun's recent publications demonstrate strong focus on cyber-physical security in power systems, distributed energy resource integration, and resilient grid operations. His work shows increasing emphasis on AI and machine learning applications for grid security and resilience, particularly in the context of high renewable penetration. His notable scientific awards include: Microsoft Software Engineering Innovation Foundation Award (2014) Best Paper Award, 2019 IEEE PES ISGT Asia Mentor of the Year, UCF Graduate Student Association (2019) Dr. Sun has successfully secured multiple research grants totaling millions of dollars from agencies including the US Department of Energy, National Science Foundation, Florida Center for Cybersecurity, and Microsoft. He currently serves as PI or Co-PI on several major projects including "Secure and Resilient Operations Using Open-Source Distributed Systems Platform (OpenDSP)" funded by the Department of Energy. He leads the Siemens Digital Grid Laboratory at UCF, which is equipped with utility-grade software and hardware including Spectrum Power Microgrid Management System, Power System Simulator for Engineering, and Siemens Distribution Feeder Automation. The lab provides capabilities for both software modeling and hardware-in-the-loop testing of power systems.
Santiago Grijalva serves as Georgia Power Distinguished Professor and Director of the Advanced Computational Electricity Systems (ACES) Laboratory at Georgia Institute of Technology's School of Electrical and Computer Engineering. He also holds the position of Associate Director for Electricity Systems at the Strategic Energy Institute (SEI). His educational background includes an Electrical Engineer degree from EPN-Ecuador (1994), M.S. in Information Systems from ESPE-Ecuador (1997), and M.S./Ph.D. in Electrical and Computer Engineering from University of Illinois at Urbana-Champaign (1999/2002). Grijalva pioneers research in decentralized power system architectures, renewable energy integration, and grid cybersecurity. His work spans smart grid technologies, electricity markets design, AI applications for power systems, and ultra-reliable grid architectures. The ACES Laboratory under his direction focuses on real-time power system control, informatics, and economics. His recent publications demonstrate strong trends in photovoltaic integration, multi-agent control systems, voltage stability analysis, and prosumer-based grid architectures, reflecting the industry's shift toward distributed energy resources and decentralized control paradigms. Georgia Tech ECE Outstanding Faculty Award Great Minds in STEM National Achievement Award ARPA-E More Than Smart Grid Disruptor Award IBM Faculty Award As principal investigator for major research projects funded by U.S. Department of Energy, ARPA-E, EPRI, PSERC, NSF, and industry sponsors, Grijalva leads initiatives modernizing electrical infrastructure. His past roles include Senior Software Developer at PowerWorld Corporation and Department Head at Ecuador's National Center for Energy Control (CENACE). He serves as Associate Editor for IEEE Transactions on Industrial Informatics and has published over 250 peer-reviewed papers. The Advanced Computational Electricity Systems (ACES) Laboratory operates at the intersection of power systems engineering and computational science, developing next-generation grid technologies for renewable integration and cyber-physical security.
Magdy M. A. Salama is a Professor and University Research Chair at the University of Waterloo's Department of Electrical and Computer Engineering, Faculty of Engineering. He holds a P.Eng. license and is a Fellow of the IEEE. His research spans Energy Systems (Power Quality, Smart Grids, Renewable Energy) and Biomedical Engineering (Medical Imaging, Sleep Analysis). He has authored/co-authored over 460 publications and supervised numerous graduate students. Education: PhD (University of Waterloo), M.Sc. and B.Sc. (Cairo University). Awards include the IEEE Fellow distinction, University Research Chair, and multiple teaching/research awards from the University of Waterloo. Research trends in his articles focus on Smart Grid resiliency, renewable integration, cyber-physical security, and biomedical applications of AI. Notable projects include voltage sag mitigation, EV fleet electrification, and blockchain-based energy trading platforms. Scientific Awards: IEEE Fellow, University Research Chair, Teaching Excellence Award (2000) Grants/Consultation: Extensive industry and institutional collaborations on power systems and biomedical tech. Labs/Teams: Active in High Voltage Lab, Smart Grids Research Group, and Medical Image Processing Lab.
Frede Blaabjerg is a Professor at Aalborg University (AAU Energy) , affiliated with the Faculty of Engineering and Science . Since 1998, he has pioneered power electronics research in applications such as wind turbines , photovoltaic (PV) systems , reliability engineering , and Power-2-X technologies. Education : PhD in Electrical Engineering (1995, Aalborg University) Honorary Degrees : Honoris Causa at University Politehnica Timisoara (2017) and Tallinn Technical University (2018) His research focuses on power electronics control , system optimization , and reliability for renewable energy and electric mobility . Recent work includes grid-forming converters , virtual synchronous generators , and smart EV charging systems. Key publication trends span 15+ years , with over 3,733 peer-reviewed articles and 900+ journal papers in power electronics , renewables , and energy storage . Notable book series: Control of Power Electronic Converters and Systems (4 volumes, Elsevier). Scientific Awards : 46 IEEE Prize Paper Awards 2020 IEEE Edison Medal 2019 Global Energy Prize 2014 IEEE William E. Newell Power Electronics Award Leadership Roles : Editor-in-Chief, IEEE Transactions on Power Electronics (2006–2012) Chairman, Danish Council for Research and Innovation Policy (2020–) President, IEEE Power Electronics Society (2019–2020)
Geert Deconinck is a full professor at KU Leuven , leading the Electrical Energy Systems and Applications (ELECTA) research group within the Department of Electrical Engineering (ESAT). He also serves as scientific leader of the EnergyVille research center's algorithms domain, focusing on smart electrical networks and thermal systems. M.Sc. and Ph.D. from KU Leuven Head of ELECTA since 2012 (10 professors, 8 postdocs, 70+ PhDs) Over 8 million EUR research budget in last 5 years 44 completed PhDs and 10 current advisees IEEE Transactions editorial board member His research spans smart grid architectures , distributed control , and cyber-physical security , with recent focus on EV-grid integration , renewable energy democratization , and multi-carrier energy systems . Current projects include: Smart Charging - E-Mobility meets Renewable Energy Early Detection and Defense Systems for Smart Grids Open-source P2P energy sharing platforms Microgrid control strategies for PV-battery systems Awarded IET Fellow and IEEE Senior Member status, his work combines machine learning with power systems engineering through both theoretical modeling and experimental validation . He has contributed over 575 publications with 9800+ Google Scholar citations.
