جست‌وجوی استاد و پژوهشگر

• Wireless Communication Systems
• Real-Time Scheduling
• Reinforcement Learning
• +۴ مورد دیگر

Dr. Ning Lu is an Assistant Professor in the Department of Electrical and Computer Engineering at Queen's University, Canada, and holds a Canada Research Chair Tier II in Future Communication Networks. He specializes in real-time scheduling, distributed algorithms, and reinforcement learning for wireless communication networks, with expertise in vehicular networks, IoT, and autonomous systems. Education : PhD in Electrical Engineering (2015), University of Waterloo MEng in Electrical Engineering (2010), Tongji University BEng in Electrical Engineering (2007), Tongji University Research Focus : Dr. Lu's work bridges theoretical foundations and practical applications in wireless networks, including vehicular communication protocols, energy-efficient systems, and AI-driven network optimization. His recent efforts emphasize autonomous vehicle motion forecasting, secure federated learning, and smart infrastructure for 6G/IoT. Publications Trends : His articles focus on cutting-edge topics like vehicular networks, reinforcement learning for edge computing, and robust AI models against adversarial attacks. Notable themes include multi-agent systems, dynamic scheduling, and hybrid communication architectures. Awards : Canada Research Chair Tier II (202X) NSERC Postdoctoral Fellowship (2015) Best Paper Award at IEEE GLOBECOM 2014 2nd Place, Valeo Innovation Challenge 2014 Contributions : He leads research on network slicing, emergency communication systems, and AI-driven traffic prediction. His work has been applied to disaster response frameworks and smart city infrastructure projects. He serves on the editorial board of Springer's Encyclopedia of Wireless Networks.

Rafajlovski Goranمشاهده پروفایل

استاد

• Electric Drives
• Power Electronics
• Energy Efficiency
• +۴ مورد دیگر

Prof. Goran Rafajlovski is a Full Professor at the Faculty of Electrical Engineering and Information Technologies (FEIT), Ss. Cyril and Methodius University of Skopje. He holds a Ph.D. in Electrical Engineering and has extensive experience in academia, industry, and diplomacy. His roles include former General Director of Electrostopyanstvo Macedonia (1998–2001) and Ambassador of the Republic of Macedonia to Germany (2001–2005). He has been a member of IEEE-IAS since 1989 and chairs the Energy Committee at the European Commission’s DG RTD-Unit K1-Energy. Education: Diploma in Electrical Engineering (1987, Skopje), M.Sc. (1991, Zagreb), Ph.D. (1996, Skopje). Research Interests: Focuses on electric drives, power quality, renewable energy integration, and energy policy. His work addresses harmonic mitigation in power systems, transformer efficiency optimization, and sustainable energy strategies for the Western Balkans. He actively participates in international conferences and advises on EU energy security policies. Professional Contributions: Over 80 publications, including seminal works on vector-controlled drives, energy efficiency in Macedonia, and renewable energy systems. Served as DAAD Alumni Club representative and chairs the Boris Trajkovski Foundation. Additional Roles: Engaged in policy-making through roles like Energy Committee member of the European Commission and guest lecturer at institutions such as the Lower Austria State Academy. His work bridges technical innovation with geopolitical and economic challenges in energy sectors.

• Energy Systems Optimization
• Renewable Energy Integration
• Flexibility Management
• +۵ مورد دیگر

Kasper Emil Thorvaldsen holds an Adjunct Associate Professor position (20% role) at NTNU's Department of Electric Energy (IEL), focusing on energy system sustainability transitions. He is primarily affiliated with the Energy and Environment study program (MTENERG) and teaches courses like TET4135 (Energy System Planning) and TET4185 (Power Markets). His main work is as a research scientist at SINTEF Energi, where he focuses on energy system optimization and flexibility valuation. Education: MSc (2013-2018) and PhD (2018-2022) in Energy Systems from NTNU, specializing in techno-economic analysis of energy storage and long-term operational planning for buildings. Research interests include energy system optimization, flexibility valuation, stochastic dynamic programming, grid tariff modeling, and electric vehicle integration. His work emphasizes practical applications in distribution systems and building energy management. Teaching highlights include coordinating TET4185 in 2024 and substituting for TET4135 in 2025. Supervision includes projects on EV charging infrastructure and grid flexibility in residential contexts. Outreach activities include media interviews and conference presentations on topics like battery economics and grid automation. He has contributed to SINTEF reports and interdisciplinary projects like the CINELDI initiative.

• Digital Image Processing
• Signal Processing
• Soft Computing
• +۵ مورد دیگر

Prof. Annamária Várkonyiné Kóczy is a Professor at the Department of Informatics within the Faculty of Economics and Informatics at J. Selye University. She holds a joint appointment as a professor at Óbuda University's Institute of Software Design and Software Development. Her academic journey includes: Electrical Engineering studies (Measurement and Control) at Technical University of Budapest (1975-1981) Mechanical Engineering degree (Mechanical Engineer-Teacher) from the same institution (1978-1983) PhD in Computer Science from Technical University of Budapest (1996) DSc (Doctor of Sciences) from Hungarian Academy of Sciences (2010) Habilitation from Széchenyi István University (2017) Her research spans digital signal processing, soft computing, and hybrid techniques for complex systems, with applications in medical diagnostics, intelligent control, and sustainable technologies. She leads projects in computational intelligence and has developed novel algorithms for real-time processing in resource-constrained environments. Recent publications demonstrate strong focus on AI-driven solutions: machine learning for bioacoustic analysis (beehive swarming), fuzzy logic optimizations for edge computing, medical imaging diagnostics (COVID-19 detection), and sustainable energy control systems. Her work consistently bridges theoretical models with practical implementations in healthcare, environmental monitoring, and industrial diagnostics. She has secured multiple research grants including: OTKA K 105846: Intelligent Space and robotics (2012-2017) OTKA K 78576: Intelligent techniques in signal/image processing (2009-2013) GVOP-3.3.1: Intelligent 3D modeling systems (2006-2007) EU Structural Funds projects on vehicle industry collaborations She mentors graduate researchers in applied informatics and leads international collaborations across Europe and Asia, focusing on intelligent systems development.

• Energy Informatics
• Blockchain Technology
• Cybersecurity
• +۸ مورد دیگر

Umit Cali is a Professor and Chair in Digital Engineering for Future Technologies at the University of York, UK, and holds a part-time Professor role in Energy Informatics at NTNU (Norwegian University of Science and Technology). He specializes in energy systems, blockchain, IT law, and data science, with over 20 years of experience in academia and industry. His research focuses on energy informatics, cybersecurity, and renewable energy integration. Education: PhD in Electrical Engineering and Computer Science (University of Kassel, Germany) and LL.M in IT and IP Law (University of Goettingen, Germany). Research Interests: Blockchain applications in energy systems, AI-driven energy management, cybersecurity for critical infrastructure, legal frameworks for digital technologies, and sustainable energy policies. Recent work emphasizes digital twin technology for energy systems optimization, decentralized energy markets, and ethical AI deployment. His publications span energy storage, smart grid cybersecurity, and policy analysis for renewable energy adoption. Professional Experience: Previously worked at IBM, Fraunhofer Institute, EnBW, and as an assistant professor at multiple universities. Serves as Vice Chair of the IEEE Blockchain in Energy Standards Working Group (P2418.5).

Dongqin Zhouمشاهده پروفایل

پژوهشگر ارشد

• Transportation Engineering
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Dongqin Zhou is a Research Fellow at the Institute for Experiential AI and The Roux Institute, Northeastern University. Their research focuses on integrating machine learning, deep reinforcement learning, and optimization techniques to address complex transportation challenges, particularly in urban traffic management and network control. Current projects involve developing scalable solutions for perimeter metering control, traffic signal optimization, and crash frequency modeling using data-driven approaches. Key technical contributions include advancing model-free control systems in urban networks and exploring transferability of AI-driven methods across different traffic environments. Work also extends to pedestrian behavior analysis using novel data sources like WiFi detection, highlighting interdisciplinary applications of transportation engineering. Publications emphasize practical implementation of AI in real-world traffic systems, balancing theoretical rigor with actionable insights for smarter urban mobility solutions.

Tong Maمشاهده پروفایل

استادیار

• Nonlinear Systems and Control
• Stochastic Control and Optimization
• Machine Learning Estimation
• +۴ مورد دیگر

Tong Ma is an Assistant Professor in the Department of Mechanical and Industrial Engineering at Northeastern University. He joined the university in July 2022 and specializes in research areas such as nonlinear systems and control, stochastic control and optimization, and data-driven methodologies. His work integrates machine learning and partial differential equations (PDEs) to address complex control challenges. Education: PhD in Mechanical Engineering from the University of Connecticut (2018) and BS in Electrical Engineering and Automation from Harbin Institute of Technology (2013). Prior to his faculty role, he served as a Postdoctoral Research Associate at Pacific Northwest National Laboratory (2019–2022) and completed an internship at Mitsubishi Electric Research Laboratories (MERL, 2018). Research focuses on advancing adaptive control strategies, Gaussian process-based stochastic predictive control, and PDE-driven systems. Recent publications emphasize methodologies for constrained tracking, uncertainty quantification, and energy grid optimization. His team actively explores applications in power systems, robotics, and advanced manufacturing. Advising includes mentoring three PhD students: Mengxu Xie (2023), Ali Mashhadireza (2024), and Siyi Yu (2024). Research collaborations extend to labs like Automation, Control, and Intelligence, with ongoing work on predictive control frameworks and physics-informed machine learning. Lab activities prioritize interdisciplinary projects combining control theory, AI, and energy systems. Future directions include scalable stochastic MPC algorithms and real-time adaptive systems for industrial applications.

• Electronics Engineering
• Smart Grids
• Embedded Systems
• +۳ مورد دیگر

Dario Petri is a Full Professor in the Department of Industrial Engineering at the University of Trento, Italy. He holds a Ph.D. in Information Engineering from the University of Padova and has held academic roles including Assistant Professor (University of Padova, 1990-1992), Associate Professor (University of Perugia, 1992-1999), and Full Professor (University of Perugia since 1999, University of Trento since 2002). He served as Head of the Department of Information Engineering and Computer Science (2010-2012) and Head of the Department of Industrial Engineering (2015-2021). His expertise spans measurement theory, signal processing, smart grids, and embedded systems. Ph.D. in Information Engineering, University of Padova (1990) M.Sc. in Electronics Engineering (summa cum laude), University of Padova (1986) His research focuses on data acquisition systems , instrumentation for smart energy grids , and application of digital signal processing to measurement problems . He has contributed to PMU algorithms, DFT-based frequency estimation, and harmonics analysis. His work intersects with metrology philosophy , examining measurement's role in empirical knowledge and decision-making frameworks. Recent publications analyze grid-following converter stability, interpolated DFT algorithms, and generative AI applications in measurement. He has authored over 400 peer-reviewed papers and received the 2020 IEEE Joseph F. Keithley Award for contributions to measurement fundamentals. As an IEEE Fellow, he chairs the IEEE Smart Cities Initiative in Trento and has held leadership roles in the IEEE Instrumentation and Measurement Society. 2020 IEEE Joseph F. Keithley Award IEEE Fellow Distinguished Reviewer & Associate Editor, IEEE Transactions on Instrumentation and Measurement Prior to his current role, Petri coordinated academic programs at the University of Perugia and University of Trento, including Ph.D., M.Sc., and B.Sc. courses. He also served on evaluation committees and contributed to IEEE conference organization.

Sriram Krishnamoorthyمشاهده پروفایل

دانشیار

• Electronic and Photonic Materials
• Wide Band Gap Semiconductors
• Power Electronics
• +۵ مورد دیگر

Sriram Krishnamoorthy is an Associate Professor in the Department of Materials at the University of California, Santa Barbara (UCSB), within the College of Engineering. His research focuses on next-generation (ultra)wide band gap semiconductors such as gallium oxide (β-Ga₂O₃), exploring their epitaxial growth, electronic transport, device design, and applications in power electronics, high-frequency electronics, and UV optoelectronics. He holds a Ph.D. in Electrical Engineering from The Ohio State University, and dual bachelor’s and master’s degrees in Physics and Electrical Engineering from Birla Institute of Technology & Science (BITS)-Pilani. His research group emphasizes interdisciplinary approaches spanning materials science, electrical engineering, and physics. Key projects include developing high-performance β-Ga₂O₃-based diodes, transistors, and photodetectors, leveraging advanced fabrication techniques like plasma-assisted molecular beam epitaxy (PAMBE) and atomic layer deposition (ALD). Recent work highlights include achieving ultra-low reverse leakage currents in Schottky barrier diodes and demonstrating kilovolt-class MOSFETs on bulk substrates. Funding sources include the National Science Foundation (NSF), Department of Energy (DOE), and Department of Defense (DoD), with collaborations extending to industry partners like Coherent/II-VI Foundation. His publications reflect a focus on dielectric engineering, defect characterization, and device scalability for grid-scale and high-frequency applications. Current research trends emphasize anisotropic properties of β-Ga₂O₃, high-k dielectric integration, and alloyed materials like β-(AlₓGa₁₋ₓ)₂O₃ to enhance device performance. The group also investigates laser-induced defects and thermal management strategies via Ga₂O₃-on-SiC composite substrates.

• Mechanical Engineering
• Information and Computing Sciences
• Electrical and Electronic Engineering
• +۳ مورد دیگر

Dr. Chen Liu is a Research Fellow at the School of Engineering, RMIT University. His research focuses on energy systems, smart grids, optimization algorithms, and the integration of renewable energy technologies. He is particularly interested in battery energy storage systems, electric vehicle (EV) infrastructure, and machine learning applications in power systems. Dr. Liu has contributed to advancing SCADA alarm management, real-time grid monitoring, and multi-objective optimization techniques. He is open to supervising Masters and PhD students in areas such as accelerated learning for neural networks and big data applications. His work emphasizes practical solutions for sustainable energy challenges, including optimal placement of EV charging stations, solar-PV integration, and frequency control in grids with high renewable penetration. Dr. Liu's research also explores data-driven approaches for energy market forecasting and grid reliability enhancement. He has published extensively in top journals and conferences, addressing topics ranging from quantum genetic algorithms to distributed training of neural networks.

• Power Electronics
• Electrical Engineering
• Renewable Energy Systems
• +۴ مورد دیگر

Dr. Carlos Teixeira is a Senior Lecturer in the School of Engineering at RMIT University, Australia. His research focuses on Power Electronics, Electrical Engineering, and Renewable Energy Systems, with a particular emphasis on Multilevel Converters, Soft Switching Techniques, and Grid-Connected Converter Design. He actively supervises research projects in areas such as thermal storage applications, common-mode mitigation in converters, and microgrid control. Research Interests Modular Multilevel Converters (MMCs) Soft Switching Strategies for DC-DC Converters Grid Synchronization and Control Microgrid Power Management High-Power Energy Conversion Systems Recent Research Trends Dr. Teixeira's recent work emphasizes advancing modular converter architectures for efficient energy storage and distribution. His publications address challenges in harmonic analysis, stability assessment of grid-tied inverters, and FPGA-based real-time simulation platforms. Key themes include optimizing ZVS operation in DAB converters, developing sensorless grid synchronization schemes, and enhancing the resilience of distributed energy systems. Supervision & Grants He oversees projects on thermal conductivity improvements for phase change materials (PCMs), decentralized phase disposition modulation for MMCs, and autonomous power management in hybrid microgrids. While specific grants are not detailed, his research aligns with RMIT's focus on sustainable energy solutions and smart grid technologies.

Manoj Dattaمشاهده پروفایل

مدرس ارشد

• Renewable Energy Systems
• Smart Grid Technology
• Energy Storage Systems
• +۳ مورد دیگر

Dr. Manoj Datta is a Senior Lecturer at RMIT University's School of Engineering, specializing in the modeling and control of renewable energy systems, energy storage, and electric vehicle integration. He holds a Chartered Professional Engineer certification and has held academic positions at RMIT since 2013 and Gifu University in Japan from 2012-2013. His research focuses on smart grids, microgrid stability, and renewable energy system optimization. Research Interests: Optimal sizing of PV, wind, and battery systems; hybrid AC/DC microgrid control; distributed generation (DG) modeling and forecasting; AI-based grid integration of energy storage and EVs; motor drives (IM, SRM, PMSG, etc.). Professional Activities: Journal reviewer for IEEE Transactions on Power Systems, Smart Grid, and others; invited speaker at IEEE conferences; technical program committee member for over 15 IEEE events. Awards include the JSPS postdoctoral fellowship (2011-2012). Teaching & Supervision: Advising on projects related to renewable energy integration, EV charging management, and grid-forming inverter stability. Open to supervising Masters and PhD students in these areas.

• Power Electronics
• Offshore Energy Systems
• HVDC Transmission
• +۲ مورد دیگر

Elisabetta Tedeschi is Professor at NTNU researching power conversion systems for offshore applications. Her work spans multi-terminal HVDC configurations, wave energy control, and grid stability for marine renewables. Current EU Horizon projects investigate energy storage deployment and hybrid offshore systems. She coordinates NTNU's involvement in the Joint Master in Marine Renewable Energy.

Seyed Amir Hosseiniمشاهده پروفایل

پژوهشگر ارشد

• Power System Reliability
• Distributed Renewable Generation
• Smart Grids Control
• +۴ مورد دیگر

Seyed Amir Hosseini is a Research Fellow at the Department of AAU Energy, Aalborg University, Denmark. He holds B.Sc., M.Sc., and Ph.D. degrees in Electrical Engineering from Sharif University of Technology (2014-2022). Previously, he was a visiting Ph.D. scholar at Denmark Technical University and a visiting researcher at RWTH Aachen University under Prof. Monti. His research focuses on power system reliability, renewable energy integration, smart grid control, and battery storage systems. Education: B.Sc. Electrical Engineering, Sharif University of Technology, 2014 M.Sc. Electrical Engineering, Sharif University of Technology, 2016 Ph.D. Electrical Engineering, Sharif University of Technology, 2022 Research interests emphasize power system stability, distributed generation, demand-side management, and advanced control strategies for renewable energy systems. Key projects include the Villum Foundation-funded RelyPES tool for reliability assessment and the RAWFaEL project on wind farm electrical systems. Publications span topics like wind farm reliability, vibration effects on IGBT modules, and frequency control using EVs and wind turbines. His work bridges theoretical advancements with practical tools for energy system resilience. Grants include leadership in RelyPES (2024-2025) and participation in RAWFaEL (2023-2024). Collaborations involve institutions like RWTH Aachen and DTU. His research contributes to both academic discourse and industry-relevant solutions.

Saeed Peyghamiمشاهده پروفایل

دانشیار

• Power Systems
• Power Electronics
• Reliability Engineering
• +۳ مورد دیگر

Saeed Peyghami is an Associate Professor at Aalborg University's Applied Power Electronic Systems department within the Faculty of Engineering and Science. He holds a PhD in Electrical Engineering from Sharif University of Technology (2017) and has been a faculty member since 2021 after a postdoc at Aalborg. His research focuses on power system reliability, power electronics control, and quantum computing applications in energy systems. He leads and collaborates on projects like SOLARIS (Horizon Europe) and Pro-Risk (Denmark), addressing renewable integration, risk modeling, and grid resilience. Key projects include designing resilient microgrids, optimizing motor drives for high-speed applications, and probabilistic risk assessment for green energy systems. He supervises four PhD students, including work on integrated motor drives and electromagnetic interference mitigation. His work contributes to UN Sustainable Development Goals related to clean energy and infrastructure. Publications emphasize reliability-driven design, microgrid stability, and EMI mitigation in power electronics. He actively publishes in journals like IEEE Access and Renewable and Sustainable Energy Reviews, focusing on both theoretical advancements and practical implementations in modern power systems.