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.
Xiongfei Wang is a Visiting Professor at KTH Royal Institute of Technology in Stockholm, Sweden, and a Digital Futures Fellow. He holds academic leadership roles, including Editor-in-Chief of IEEE Transactions on Power Electronics and chairs in IEEE committees. His research focuses on power electronics systems, stability analysis, and data-driven approaches for energy systems. Previously, he served as a Professor at Aalborg University (2009–2022). His work addresses challenges in power system stability, converter dynamics, and renewable integration. He leads projects like 'Machine Learning for Dynamics Analysis of Power Electronic Systems,' aiming to enhance grid resilience through AI-driven methods. Notable awards include IEEE Fellow (2023), Isao Takahashi Award (2022), and multiple best paper awards. Wang collaborates extensively, organizing conferences and editing journals. His research spans power electronics, grid stability, and smart grid technologies, with a focus on practical applications in energy transition.
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.
Mustafa A. Mustafa is a Senior Lecturer (Associate Professor) in the Department of Computer Science at The University of Manchester, where he leads the Trusted Digital Systems Cluster as part of the university-wide Centre for Digital Trust and Society. His academic journey spans prestigious institutions including The University of Manchester, where he completed his PhD, and KU Leuven in Belgium, where he served as a post-doctoral research fellow. Dr. Mustafa earned his educational qualifications through an impressive academic path: a B.Sc. in communications from the Technical University of Varna, Bulgaria (2007), an M.Sc. in communications and signal processing from Newcastle University, UK (2010), and a Ph.D. in computer science from The University of Manchester, UK (2015). His doctoral research focused on "Smart Grid Security: Protecting Users' Privacy in Smart Grid Applications," laying the foundation for his subsequent research career. Dr. Mustafa's research expertise centers on information security, data privacy, and applied cryptography with particular focus on smart grid systems, smart city applications, e-health, and IoT. His work addresses critical challenges in securing peer-to-peer electricity trading markets, smart metering infrastructure, electric vehicle charging systems, and health data management. He has developed innovative solutions for keyless car sharing systems, frictionless authentication mechanisms, and privacy-preserving protocols for data collection and distribution. His scholarly contributions demonstrate a consistent trajectory toward increasingly sophisticated privacy-preserving techniques applied across multiple domains. Recent work shows a growing integration of artificial intelligence and machine learning approaches with traditional cryptographic methods, particularly in federated learning systems and large language model verification. His research bridges theoretical cryptography with practical implementations in energy systems and healthcare applications. Dr. Mustafa's scientific achievements have been recognized with several prestigious awards: Winner of the Student Video Competition at IEEE SmartGridComm 2017 for "Secure and Privacy-friendly Local Electricity Trading" Best Paper Award at SECURWARE 2017 Distinguished Achievement Award as Postgraduate Research Student of the Year nominee by the School of Computer Science of The University of Manchester (2015) Dame Kathleen Ollerenshaw Research Fellowship (2018-2023) As an academic supervisor, Dr. Mustafa has mentored numerous graduate students through their PhD and Master's research, with a particular focus on privacy and security challenges in emerging technologies. His current supervision portfolio includes research on privacy-friendly multi-agent systems for smart grids, security for IoT in e-health, vulnerability detection in IoT cryptography, and bot detection systems. He has secured significant research funding through multiple competitive grants including EnnCore: End-to-End Conceptual Guarding of Neural Architectures (EPSRC, 2020-2024), SCorCH: Secure Code for Capability Hardware (EPSRC, 2019-2023), and SNIPPET: Secure and Privacy-friendly Peer-to-peer Electricity Trading (FWO-SBO project, 2019-2023). Dr. Mustafa leads the Trusted Digital Systems Cluster within the Centre for Digital Trust and Society at The University of Manchester. His research group comprises PhD students, postdoctoral researchers, and collaborators working on cutting-edge security and privacy solutions. The team maintains strong international collaborations, particularly with KU Leuven in Belgium, and contributes to standards development as evidenced by Dr. Mustafa's role as an expert in the IEC/SYC/WG 3 "IEC Smart Energy Roadmap."
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.
Deepa Kundur is the Professor & Chair of The Edward S. Rogers Sr. Department of Electrical & Computer Engineering at the University of Toronto. She earned her BASc, MASc, and PhD in Electrical and Computer Engineering from the same institution in 1993, 1995, and 1999, respectively. Current roles: IEEE Spectrum Advisory Board Conference leadership: General Chair of 2018 GlobalSIP Symposium, TPC Co-Chair for IEEE SmartGridComm 2018, among others Her research focuses on cybersecurity , signal processing , and complex dynamical networks , particularly in smart grid applications. She has authored over 200 publications and pioneered techniques for detecting false data injection attacks, enhancing grid resilience, and integrating machine learning into power systems. Her recent work spans quantum learning for grid security , LLM-based mental health prediction , and resilient control systems . She has received 14 best paper recognitions, including IEEE SmartGridComm (2015) and IEEE INFOCOM Workshop (2008). Fellowships: IEEE Fellow (2015), Canadian Academy of Engineering Fellow (2016), Massey College Senior Fellow (2019) Teaching awards: Tenneco Meritorious Teaching Award (2005), Gordon Slemon Teaching of Design Award (2002) Early career honors: NSERC Scholarships (PGS A/B), Canada Scholarship She leads the Kundur Research Group , developing models for cyber-physical systems in smart grids and autonomous vehicle networks. Her team explores reinforcement learning for grid defense , transmissibility-based fault detection , and privacy-preserving smart grid analytics .
Professor Li Hui serves as the executive dean of the School of Network and Information Security at Xidian University, where he holds the position of second-level professor and doctoral supervisor. He is nationally recognized as a distinguished teacher and serves in multiple prestigious roles including member of the National Steering Committee for Postgraduate Education in Cryptography, inaugural president of ACM SIGSAC CHINA, and director of several major academic societies related to cryptography and information security. Professor Li's research spans cryptographic information security, privacy computing, information theory, and coding theory, with significant contributions to network and cyberspace security. His work demonstrates a strong focus on both theoretical foundations and practical applications, particularly in developing security protocols for emerging technologies like blockchain, federated learning systems, and IoT environments. His research output shows consistent innovation in balancing security requirements with computational efficiency across diverse application domains. With over 300 publications and more than 15,000 Google Scholar citations (H-index 60), Professor Li's scholarly impact is substantial. His recent publications demonstrate increasing emphasis on privacy-preserving machine learning, secure multi-party computation, and cryptographic protocols for distributed systems, reflecting the evolving security challenges in the AI era. Three second-class national teaching achievement awards Special prize and first-class national teaching achievement awards Four first-class provincial and ministerial science and technology progress awards Privacy Computing Theory award (Qian Weichang Chinese Information Processing Science and Technology Award) Multiple patents with over 80 granted inventions Professor Li leads the Cyber Changan Team and serves as head of the Shaanxi Provincial Innovation Team for Mobile Internet Security. He has successfully supervised numerous doctoral and master's students who have gone on to win prestigious competitions like the National College Student Information Security Competition. His research is supported by major national grants including a National Key R&D Program project and key projects from the National Natural Science Foundation of China.
Dr. Prabodh Bajpai is a Professor in the Department of Sustainable Energy Engineering at the Indian Institute of Technology Kanpur. Previously, he served as an Associate Professor at the same department from July 2022 to December 2022, and before that at the Electrical Engineering Department of IIT Kharagpur from July 2014 to June 2022. He began his academic career as an Assistant Professor at IIT Kharagpur from June 2008 to July 2014. His educational background includes a Ph.D. in Electrical Engineering (Power Systems) from IIT Kanpur (2008), M.Tech in Energy Studies from IIT Delhi (2001), and B.E. in Electrical Engineering from IIT Roorkee (1997). Dr. Bajpai's research spans renewable energy integration, power system operation and control, microgrid technologies, and smart grid applications. His work focuses on practical implementation of sustainable energy solutions with emphasis on power electronics, energy storage, and grid stability. He has made significant contributions to the fields of distributed generation integration, protection schemes for renewable-rich systems, and energy management in microgrids. His recent publications show a strong focus on DC microgrids, multi-port power converters, and advanced control strategies for renewable integration. The research demonstrates increasing sophistication in power electronics applications for sustainable energy systems, with particular emphasis on practical implementations for commercial and agricultural applications. Dr. Bajpai actively mentors graduate students, currently supervising seven students across PhD and M.Tech programs. His teaching portfolio includes core courses in electrical power engineering, renewables-integrated smart power systems, and energy systems modeling and analysis at IIT Kanpur, building on his extensive teaching experience at IIT Kharagpur where he developed several new courses in renewable energy systems. His research group maintains a Hybrid AC/DC Microgrid test facility and has developed a Renewable Hybrid Energy Power Plant for stand-alone applications, demonstrating his commitment to translating theoretical research into practical implementations.
Prof. Maryline Laurent is a Professor at Telecom SudParis, affiliated with the SAMOVAR research laboratory. Her work focuses on cybersecurity, privacy-preserving technologies, blockchain applications, and IoT security. She has contributed to numerous high-impact publications and conferences, addressing challenges in secure healthcare systems, decentralized identity management, and privacy in distributed systems. Her research spans cryptographic protocols, access control mechanisms, and compliance with EU data protection regulations. Key areas of expertise include secure communication protocols for IoT, blockchain-based solutions for healthcare, and privacy-enhancing technologies. She has collaborated on projects such as self-sovereign identity frameworks, anonymized data aggregation, and privacy-preserving smart grid systems. Her work emphasizes practical methodologies for assessing re-identification risks in anonymized datasets and designing secure systems compliant with evolving regulations. Prof. Laurent’s contributions extend to book chapters and edited volumes on digital identity management and wireless network security. She actively participates in international conferences and initiatives, advocating for privacy-by-design principles in intelligent infrastructures.
John Byrne is a Distinguished Professor of Energy and Climate Policy and Director of the Center for Energy and Environmental Policy (CEEP) at the University of Delaware's Biden School of Public Policy. His academic career spans over three decades with significant contributions to global climate policy through roles in the IPCC, World Council for Renewable Energy, and Seoul International Energy Advisory Council. He pioneered the Sustainable Energy Utility (SEU) model and led the first SEU implementation in Delaware, recognized internationally for its innovative financing mechanisms. His research focuses on energy transitions, environmental justice, and renewable energy integration. Notable achievements include co-founding the International Solar Cities Initiative, advising China’s State Environmental Protection Agency, and conceiving the SEU's AA+-rated bond program. Byrne has held visiting positions at Lawrence Berkeley National Laboratory and Seoul National University, where he contributed to South Korea’s greenhouse gas abatement strategy. Byrne’s publications include 19 books and 170+ articles, with influential works like Rethinking Environmentalism (MIT Press) and Green Energy Economies . He serves as Co-Editor-in-Chief of WIREs Energy and Environment and editor of the Energy and Environmental Policy book series since 1983. His work is funded by major institutions including the World Bank, UNDP, and U.S. Department of Energy. Key recognitions include the 2007 Nobel Peace Prize (shared via IPCC contributions) and Fulbright Senior Lecturer Award. Byrne’s current efforts focus on advancing solar energy policies, sustainable urban development, and bridging environmental justice with climate resilience.
Guodong Shi is Associate Professor at the University of Sydney's Australian Centre for Robotics, heading the Centre for Robotics and Intelligent Systems. His research develops theoretical frameworks for multi-agent coordination, distributed optimization, and networked control systems. Current projects investigate collective decision-making under information constraints, privacy-preserving optimization, and game-theoretic formulations for social and robotic networks. His group develops algorithms for distributed solution of linear equations, Boolean networks, and equilibrium seeking. Doctoral supervision includes projects on acrobatic legged robots, reinforcement learning for robotic stability, and safe control under dynamic environments. Laboratory capabilities support theoretical and experimental validation. Research has applications in autonomous swarm robotics, smart grid optimization, and social network analysis. Teaching includes graduate courses on networked systems and optimization.
Professor Ibrahim Khalil is a faculty member in the School of Computing Technologies at RMIT University, Melbourne, Australia. He holds a PhD in Computer Science from the University of Bern (2003) and has extensive industry experience in Silicon Valley focusing on secure network protocols. His research spans Security, Privacy, Federated Learning, Blockchain, Quantum Computing, and Distributed Systems. He leads high-impact projects funded by ARC grants (DP250100582, DP220100215, etc.) and international initiatives like the EU’s SELFY project. His work addresses challenges in secure AI data analytics, privacy-preserving systems, and critical infrastructure protection. Khalil supervises PhD/Masters students on topics ranging from federated learning security to quantum-enhanced machine learning. Education: PhD in Computer Science (University of Bern, 2003); prior roles at EPFL, Osaka University, and industry tech hubs. Research Interests: Privacy-Preserving Technologies Blockchain Applications in Healthcare and Supply Chains Quantum Computing for Machine Learning Secure Edge Computing and Federated Learning IoT Security and Critical Infrastructure Protection Grants & Collaborations: Over 10 major grants since 2017, including ARC Discovery/Linkage Projects and international partnerships (QNRF, EU). Notable projects include Privacy-Aware Digital Twins for Critical Infrastructure and Federated Learning frameworks for GenAI models. Advising & Labs: Active supervisor of 25+ research projects since 2013, focusing on anomaly detection, secure data analytics, and blockchain-based systems. Collaborates with industry partners on defense and healthcare tech.
Amir Asif is a Professor at the Lassonde School of Engineering, York University, and concurrently serves as Vice President, Research and Innovation. His academic leadership roles include Dean of the Gina Cody School of Engineering and Computer Science at Concordia University (2014-2020). He specializes in signal processing, communications, and their applications in healthcare, power grids, and distributed systems. Asif holds a PhD from Carnegie Mellon University and a Harvard certification in executive leadership. Education: PhD, Electrical and Computer Engineering, Carnegie Mellon University (1996) MS, Electrical and Computer Engineering, Carnegie Mellon University (1993) BSc, University of Engineering and Technology Lahore (1990) Harvard Certificate in Leadership for Senior Executives (2018) Research Interests: Asif’s work spans signal processing for medical imaging (e.g., ultrasound elastography), smart grid optimization, and cybersecurity in power systems. His recent publications address hydrogen energy systems, EMG-based gesture recognition, and resilient control frameworks against cyberattacks. Grants & Leadership: He leads NSERC-funded projects on federated learning and resilient algorithms. He chairs the Ontario Council of University Research and serves on TRIUMF Innovations and the Richmond Hill Board of Trade. His grants include SSHRC funding for equity initiatives and NSERC support for distributed signal processing. Teaching & Mentorship: Asif has supervised over a dozen graduate students and taught courses like Digital Communications and Statistical Signal Processing Theory. Notable advisees include Arash Mohammadi (PhD, 2014) and Nick Sajadi (PhD, 2017).
Mark Fagan is a Lecturer in Public Policy at Harvard Kennedy School, with affiliations to the Mossavar-Rahmani Center for Business and Government, Taubman Center for State and Local Government, and Center for Public Leadership. He teaches courses on operations management, policy design, and supply chain management. Previously, he was a Lecturer in Law at Boston University School of Law and a consultant at Norbridge, Inc. Education: MA in City and Regional Planning from Harvard University (199X), BA from Bucknell University (19XX). Research focuses on regulatory policy in competitive markets, autonomous vehicles, transportation systems, and energy markets. Key initiatives include leading the Autonomous Vehicle Policy Scrums initiative and publishing Supply Chain Management: A Public Sector Perspective (2024). His work examines how public policy can optimize supply chains while addressing geopolitical, environmental, and equity challenges. Teaching materials include digital courses on lobbying and advocacy, operations management case studies, and the Architect, Pilot, Scale, Improve policy implementation framework. Professional activities include advising governments on cross-sector policy design and consulting for private-sector clients in transportation, utilities, and telecommunications industries.
