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نمایش ۷۲۱-۷۳۵ از ۱٬۳۴۵ استاد راهنما
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Chris Diduch is a Professor in Electrical and Computer Engineering at the University of New Brunswick. His research develops control strategies for power systems with high renewable penetration, focusing on voltage regulation and microgrid management. Key research areas: Smart grid optimization algorithms Renewable energy integration Demand-side management systems
دانشیار
Professor Kristen Schell is an Associate Professor in the Department of Mechanical and Aerospace Engineering at Carleton University, joining in July 2020. She holds dual PhDs in Engineering from Carnegie Mellon University and the University of Porto, alongside degrees from Johns Hopkins and Carnegie Mellon. Her research focuses on renewable energy integration, including wind power modeling, electricity market dynamics, and policy design for sustainable energy systems. B.S. Chemical Engineering - Carnegie Mellon University M.S.E. Environmental Engineering - Johns Hopkins University Dual Ph.D. Engineering - Carnegie Mellon University & University of Porto Her work combines machine learning and optimization to address energy transition challenges, leveraging empirical datasets from utilities and climate models. She previously held roles at Rensselaer Polytechnic Institute (RPI) and Polytechnique Montréal, contributing to a US DOE ARPA-E grant. Currently leads the APEX lab, offering a PhD position in Physics-informed Deep Learning for Wind Power. No individual scientific awards listed, though part of team-awarded DOE funding. Active in federal-to-community energy policy advising.
استادیار
Seulchan Lee is Assistant Professor of Operations Management at Michigan Technological University's College of Business. He holds a PhD from Texas A&M University with expertise in sustainable operations. Research Focus: Develops optimization models for complex operational challenges, particularly: Sustainable supply chain design Retail operations innovation Renewable energy systems management Logistics collaboration frameworks Publication Trends: Recent work demonstrates strong methodological focus on: Game theory applications in operations Econometric analysis of operational decisions Blockchain-enabled energy systems Cross-docking supply chain optimization Professional Engagement: Active in INFORMS and POMS communities, serving as session chair and conference committee member.
Alexandra M. Newman is a Professor in Mechanical Engineering at Colorado School of Mines and serves as the Director of the Operations Research with Engineering Program. Her research focuses on applied optimization across diverse domains including mining, energy systems, healthcare, and sports scheduling. Education: BS in Applied Mathematics, University of Chicago MS in Operations Research, University of California, Berkeley PhD in Industrial Engineering and Operations Research, University of California, Berkeley Her work addresses complex logistical challenges in underground mine planning, renewable energy deployment, and counterinsurgency modeling. Recent publications emphasize microgrid resilience, electric vehicle energy consumption, and optimization of hybrid solar power systems. Notable research trends include: Integration of sustainability metrics in mining and energy systems Advancements in dispatch optimization for renewable energy Application of stochastic modeling to athletic and healthcare scheduling
Mahshid Amirabadi is an Associate Professor in the Department of Electrical and Computer Engineering at Northeastern University. Her research focuses on power electronics for renewable energy systems, microgrids, variable speed drives, and wireless power transfer. She holds a PhD from Texas A&M University and has held academic positions at the University of Illinois at Chicago and Northeastern University since 2013. Education PhD, Electrical Engineering (Power-Power Electronics), Texas A&M University (2013) MS, Electrical Engineering (Power-Power Electronics), University of Tehran (2006) BS, Electrical Engineering (Electronics), Shahid Beheshti University (2002) Research Interests Dr. Amirabadi’s work centers on designing efficient and reliable power converters, particularly for renewable energy integration and high-frequency applications. She develops universal converters to streamline energy conversion processes across various systems. Key Awards NSF CAREER Award (2021) IEEE Transactions on Power Electronics Best Paper Awards (2020, 2021) Best Paper at IEEE ECCE (2016) Grants & Advising She leads NSF-funded research on universal SiC-based converters and has secured grants from the Office of Naval Research and ARPA-E. Her advisees include PhD students Ehsan Afshari and M. Khodabandeh, contributing to impactful publications in top journals. Labs & Teams Her lab focuses on advanced converter topologies and their applications in renewable energy systems, collaborating on projects like ARPA-E’s universal power converter initiatives.
مدرس ارشد
Dr. Jiajia Yang is a Senior Lecturer in Renewable Energy and Electrical Engineering at James Cook University (JCU), Australia. He holds a Ph.D. from the University of New South Wales (2018) and has extensive experience in power system modeling, renewable integration, and energy markets. Prior to JCU, he worked as a Senior Research Associate at UNSW and a Senior Power System Engineer in industry projects like the Renewable Energy Zone (REZ) programs. Education: B.E., Northeast Electric Power University, China (2011) M.E., Zhejiang University, China (2014) Ph.D., University of New South Wales, Australia (2018) Research Interests: Data science in smart grids Electricity markets for renewable-rich systems Localized/P2P trading mechanisms Hydrogen economy Recent Research Trends: Dr. Yang’s work focuses on decarbonizing power systems through innovative market designs, renewable integration, and cybersecurity. His 2024 studies emphasize hydrogen credit frameworks and carbon-neutral energy systems, while earlier projects address P2P trading and grid stability under high renewables. Awards: Outstanding Editorial Board Member (2023) Best Research Paper Award (2018) Advising & Grants: He coordinates teaching modules like Power Engineering 1/2 and leads the 2024 International Conference on Energy and Environment Engineering. His research is supported by projects like the North Queensland Transmission Grid Planning initiative (2024–2027). Labs/Teams: Engaged in IEEE PES roles, including IEEE Transactions on Industry Applications editorial work and chairing multiple conferences.
Overview Fangxing 'Fran' Li is the John W. Fisher Professor in the Min H. Kao Department of Electrical Engineering and Computer Science (EECS) at the University of Tennessee, Knoxville (UTK), and Director of the NSF-funded Center for Ultra-wide-area Resilient Electrical Energy Transmission Networks (CURENT). He holds IEEE and IET Fellowships and serves as Editor-in-Chief of the IEEE Open Access Journal of Power and Energy. His research focuses on power systems resilience, renewable integration, and computational methods. Education PhD in Electrical Engineering, Virginia Tech (2001) MSEE, Southeast University, China (1997) BSEE, Southeast University, China (1994) Research Interests Dr. Li’s work emphasizes microgrid control , energy markets , machine learning applications , and grid resilience . He leads the ENLITEN Lab, advancing smart grid technologies and large-scale testbeds like CURENT LTB, which earned an R&D 100 Award in 2020. Awards & Recognition Recipient of the R&D 100 Award , UTK Chancellor’s Research Award , and numerous IEEE paper awards. His students have won top accolades at IEEE conferences and CURENT events. Labs & Teams Directs CURENT and oversees the ENLITEN Lab, collaborating with Oak Ridge National Laboratory (adjunct role). His team maintains a large-scale testbed and explores cutting-edge solutions for grid challenges.
Antonella Ferrara is a Full Professor of Automatic Control at the University of Pavia's Department of Electrical, Computer and Biomedical Engineering (ECBE). She holds leadership roles, including Head of the Intelligent Robotics Laboratory and President of the Department's Research Standing Committee. Her academic journey includes a Laurea Degree (MSc equivalent) in Electronic Engineering from the University of Genova (1987) and a PhD in Computer Science and Electronics (1992). She transitioned from Assistant to Full Professor at the University of Pavia, contributing significantly to nonlinear control, automotive systems, robotics, and power systems. Her research focuses on sliding mode control, vehicular traffic modeling, and applications in autonomous systems. She has authored/co-authored over 450 publications, including 160 journal papers and monographs on topics like vehicle dynamics and freeway traffic control. Awards include IEEE Fellow (2020), IFAC Fellow (2021-2023), and AAIA Fellow (2024). She teaches courses such as Process Control, Robot Control, and Nonlinear Control in English, and contributes to international collaborations, including projects on sustainable mobility and medical robotics. Her institutional roles span research leadership, international mobility coordination, and editorial contributions to journals like Automatica and IEEE Transactions. Prof. Ferrara supervises numerous PhD, postdoc, and graduate students, leading over 200 MSc theses since 2020. She chairs major conferences, including the 24th IFAC World Congress (2029) and the 2024 IEEE Workshop on Variable Structure Systems. Her work bridges theoretical advancements with practical applications in industry, including collaborations with automotive companies like Ferrari F1 and FIAT.
Walter O. Krawec is an Associate Professor of Computer Science at the University of Connecticut. His research focuses on quantum cryptography and quantum information theory, particularly exploring quantum resources in cryptographic applications and entropic uncertainty relations. He advises students at all levels and leads a research group with active projects in quantum key distribution (QKD), quantum networks, and secure microgrids. Research Interests: - Quantum Cryptography and Quantum Key Distribution (QKD) - Entropic Uncertainty Relations - Quantum Network Security and Protocols - High-Dimensional Quantum Systems - Semi-Quantum Communication Protocols - Quantum Sampling and Resource Analysis Key Research Trends in Articles: His work spans theoretical security proofs for QKD protocols, practical implementations in satellite and hybrid networks, and applications to power grid security. Recent efforts emphasize optimizing key rates, mitigating quantum noise, and developing protocols compatible with NISQ devices. Scientific Awards: None explicitly listed in provided texts. Advising & Grants: - Advised over 15 students (PhD, MS, Undergraduate) since 2016. - Involved in NSF grants like 'CAREER: Hybrid Approaches to Quantum Cryptography' and 'CIF: Small: Secure Quantum Communication with Limited Resources.' - Developed open-source software tools for QKD protocol analysis and simulation. Labs/Teams: Collaborates with interdisciplinary teams on quantum networks, including work with JPMorgan Chase's Future Lab and power grid security initiatives.
Alessandro Bosisio is a Researcher at the Department of Industrial and Information Engineering, University of Pavia. His research focuses on power distribution systems, renewable energy integration, smart grid technologies, and machine learning applications in energy systems. He has conducted extensive studies on voltage control, fault prediction in distribution grids, and optimization algorithms for grid reliability and resilience. Key research areas include: Impact of extreme weather on power systems Renewables-to-hydrogen systems Machine learning for load forecasting and grid automation GIS-based planning for distribution networks His work emphasizes real-world case studies in Milan and other Italian regions, addressing challenges such as electromobility integration, grid digitalization, and energy transition strategies. Bosisio has also contributed to patents related to distribution network reconfiguration and smart grid automation systems.
YangQuan Chen is a Professor in the Department of Mechanical Engineering at the University of California, Merced. His research focuses on unmanned aircraft systems, mechatronics, renewable energy systems, cyber-physical systems, and applied fractional calculus. He leads multiple labs, including locations at SE2-273 and 4225 N. Hospital Rd., Atwater, CA. His work integrates advanced control theory, robotics, and digital twin frameworks for applications in environmental monitoring, precision agriculture, and energy systems. Education: PhD (1998) from Nanyang Technological University, Singapore; M.S. (1989) and B.S. (1985) from Chinese institutions. His research emphasizes interdisciplinary approaches, combining fractional calculus with machine learning for real-world challenges like pandemic modeling, UAV-based emission tracking, and smart agriculture. Key research areas include: Unmanned Aircraft Systems (UAS) for environmental and agricultural applications Cyber-physical systems and digital twin frameworks Applied fractional calculus in control systems and epidemiology Machine learning for soil carbon sensing and crop monitoring Recent work explores UAV swarms for methane emission quantification, battery health-aware mission planning, and physics-informed neural networks for state estimation. His lab develops innovative solutions for renewable energy systems, such as adaptive controllers for proton exchange membrane electrolyzers and robust consensus strategies for multi-agent systems. Awards and recognition include prominent citations on Google Scholar and ResearchGate. Ongoing projects involve collaboration with industry and government agencies on smart agriculture, environmental sensing, and energy efficiency.
Anthony Papavasiliou is an Assistant Professor at the School of Electrical and Computer Engineering, National Technical University of Athens (NTUA). Previously, he held the ENGIE Chair as an Associate Professor at Université catholique de Louvain (UCLouvain) and received the 2018-2021 Franqui Foundation Research Professorship. His research focuses on operations research, electricity market design, power system operations, and renewable energy integration. He holds a BSc from NTUA and MSc/PhD from UC Berkeley, where he collaborated with Professor Shmuel Oren. Education: BSc: Electrical and Computer Engineering, NTUA MSc/PhD: Industrial Engineering & Operations Research, UC Berkeley Research Interests: His work addresses challenges in energy systems optimization, market design for decarbonized grids, stochastic programming, and the integration of distributed energy resources. Key areas include: Electricity market mechanisms Uncertainty management in power systems Flexibility valuation Grid reliability under renewables Awards & Grants: ERC Starting Grant (2019) Bodossaki Foundation Award (2021) INFORMS Best Publication Awards (2015, 2021) Advising & Grants: He leads the ICEBERG research group and has advised on projects for TSOs, regulators, and utilities. His work includes: EU-funded projects on market design Consulting for energy policy development Lab & Teams: Active in the ICCS laboratory and collaborates with international teams on smart grid innovation, particularly in cross-border balancing and zonal pricing frameworks.
Aleksei Tepljakov is a Senior Researcher at Tallinn University of Technology's Department of Computer Systems, specializing in fractional-order control systems and intelligent automation. His research develops novel methodologies for robust control design. Research focuses on fractional-order PID controllers, robust stabilization techniques, and data-driven control applications in power systems and industrial processes. Recent work integrates digital twin technology for virtual commissioning of control systems. Publications emphasize computational approaches to stability analysis in time-delay systems and practical implementations in energy systems. Article trends show consistent innovation in fractional calculus applications for industrial control challenges. Leads research in extended reality interfaces for control engineering and digital twin implementation frameworks.
Eduard Petlenkov is a Tenured Full Professor at the Department of Computer Systems at Tallinn University of Technology (TalTech), leading the Centre for Intelligent Systems. His research focuses on advanced control systems, energy efficiency, robotics, and artificial intelligence applications. He holds the award of Recognized Lecturer 2023 . Key research areas include: Fractional-order control systems Data-driven optimization for energy systems Robotics and autonomous systems Model predictive control (MPC) Power grid stability and renewable integration Recent work emphasizes: Stabilization techniques for hybrid power systems Radar technologies for unmanned ground vehicles Energy harvesting in metamaterials Real-time control of unknown linear systems Smart grid digital twin frameworks His contributions span 20+ peer-reviewed articles (2022–2025), addressing topics like reinforcement learning in microgrid control and fractional-order PID tuning methods. Active in bridging industry 5.0 education through blended learning approaches.
استادیار
Seyyedmohsen Azizi is an Assistant Professor in the School of Applied Engineering and Technology at New Jersey Institute of Technology. His research focuses on control systems, fault diagnosis, and renewable energy integration. He has led projects funded by the National Science Foundation and Natural Sciences and Engineering Research Council of Canada. Education: Ph.D. in Engineering (inferred from academic rank) Key research areas include satellite formation flight control, fault detection in power systems, and decentralized control of wind-diesel hybrid systems. His work combines machine learning with traditional control theory for robust system design. Active grants include the Renewable Energy Systems Training (REST) Laboratory Development and Workforce Training project (2019-2023) and multiple fault diagnosis initiatives in satellite constellations since 2007. No scientific awards explicitly listed in profile. Advising focuses on graduate students working in control systems and renewable energy. He collaborates on interdisciplinary projects involving aerospace and electrical engineering.
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