جست‌وجوی استاد و پژوهشگر

• Electric Drives
• Power Electronics
• Sensorless Control Systems
• +۳ مورد دیگر

Lennart Harnefors serves as a Visiting Professor in the Department of Electrical Engineering and Automation at Aalto University. His research focuses on advanced control systems for electrical drives and power electronics, with particular expertise in sensorless control methodologies and grid-forming converter technologies. His primary research areas include Electric Drives , Power Electronics , and Sensorless Control Systems , with significant contributions to observer design for motor drives and grid synchronization techniques. Recent work demonstrates innovative approaches to closed-form observer design and power-synchronization control for modern power systems. His publication trends reveal concentrated activity in high-impact electrical engineering domains, particularly sensorless control algorithms (40%), grid-forming converter technologies (30%), and observer-based estimation methods (30%). These works frequently address industrial implementation challenges in renewable energy integration and motor drive systems. Scientific Awards: IEEE International Symposium on Sensorless Control for Electrical Drives: Second Prize Paper Award (2023) for 'Speed-adaptive full-order observer revisited: Closed-form design for induction motor drives' Professor Harnefors actively collaborates with researchers across multiple institutions, evidenced by his co-authorship on recent publications. His work demonstrates strong industry relevance with applications in industrial automation and renewable energy systems. Current research efforts focus on advancing sensorless control frameworks for next-generation electrical drive systems.

• Electrical Machines
• Renewable Energy Systems
• Smart Grids
• +۵ مورد دیگر

Karlis Athanasios serves as Associate Professor, Director of the Electrical Machines Laboratory, and Vice President at the Department of Electrical and Computer Engineering (THMMY) of the Aristotle University of Thessaloniki. He holds Senior Member status in IEEE and serves on the Board of Directors of the Hellenic Institute of Electric Vehicles (ELINHO). His research spans electromobility, electrical machines, renewable energy systems, smart grids, and energy automation . Key focuses include diagnostic methods for electrical machines, microgrid integration, and techno-economic evaluation of power generation systems. He pioneered the donation of an electric car (Jmstar MBG3000 EV) to the Electrical Machines Laboratory for student research. Awarded the 2015 IEEE Outstanding Branch Chapter Advisor Award (Region 8) and 2016 IEEE IAS Outstanding Student Branch Chapter Advisor Award , he organized the 23rd International Conference on Electrical Machines (ICEM 2018) with 450 participants from 45 countries. His publication trends emphasize real-time energy management, fault diagnosis in motors, and renewable integration using AI-driven control systems. 2015 IEEE Outstanding Branch Chapter Advisor Award, Region 8 2016 IEEE IAS Outstanding Student Branch Chapter Advisor Award He supervises three doctoral theses and leads the Electrical Machines Laboratory, which focuses on control and diagnostic methods for electrical machines. His research program PRENED '97 investigated small hydroelectric stations, and he maintains active collaborations with international institutions including Virginia Tech and Friedrich-Alexander-Universität Erlangen-Nürnberg.

George Papafotiouمشاهده پروفایل

استاد

• Power Electronics
• Model Predictive Control (MPC)
• Renewable Energy Systems
• +۳ مورد دیگر

George Papafotiou is a Full Professor in the Department of Electrical Engineering at Eindhoven University of Technology (TU/e) and Head of the Power Electronics Lab. His research focuses on computational intelligence, particularly Model Predictive Control (MPC), applied to power electronics systems for applications in renewable energy, high-efficiency power conversion, and grid integration. He holds affiliations with the EIRES Research Institute and the Cyber-Physical Systems Center in Eindhoven. Academic Background: Papafotiou earned his PhD in Electrical Engineering from Aristotle University of Thessaloniki (2002) and completed a postdoc at ETH Zurich (Switzerland). He spent 15 years at ABB in roles including Scientist, Global R&D Manager for SW/Control HW, and Quality Manager, leading projects on MPC-based control systems for industrial drives and energy management. Research Interests: His work centers on advancing power electronics through MPC for microsecond-scale control, enabling reliable systems critical to a carbon-free future. Key areas include modular multilevel converters (MMCs), soft-switching techniques, grid-tied power electronics, and harmonics mitigation in high-voltage systems. Projects: Current projects include RelSST: Developing reliable solid-state transformers for smart grids. HiVECAF: Designing versatile, efficient active filters for power quality improvement. Teaching: He teaches Electric Circuits Analysis for Energy Conversion Electric Drive Systems Grants & Labs: Leads the Power Electronics Lab, focusing on applied research in sustainable energy systems and industrial automation.

• Condition Monitoring
• Fault Analysis
• Electrical Systems Modelling
• +۴ مورد دیگر

Dr Nur Sarma is an Assistant Professor in the Department of Engineering at Durham University, specializing in renewable energy systems and electrical engineering. Their research focuses on condition monitoring, fault analysis, and control strategies for electrical machines and power systems. They teach ENGI4467 and ENGI44T10 Electrical Energy Conversion modules since 2022. Education: PhD Scholarship from Turkish Ministry of Education (2011) International Postdoctoral Research Fellowship (TÜBİTAK, 2019) Research Interests: Renewable energy system optimization Electrical machine fault diagnosis Advanced power electronics control Grid integration solutions Key Contributions: Recent work includes DC-DC converter designs, battery storage management, and fiber optic sensing for machinery health monitoring. Publications span condition monitoring techniques, power quality analysis, and wind turbine fault detection. Awards: Best Paper Prize (ICRERA 2016) Women in Energy Empowerment Programme Scholarship (2021-2022) EPSRC EDI+ Fellow Professional Roles: EDI and Wellbeing Director at Durham Engineering Mentoring Coordinator for IEEE Women in Power Group Organizing Committee Member for Women in Engineering Sessions (ECCE Europe 2025) Collaborations: Active in Supergen ORE Hub mentoring and IEEE Women in Engineering initiatives.

Gregory S. Chirikjianمشاهده پروفایل

استاد

• Robotics
• Controls
• Computer Vision
• +۶ مورد دیگر

Gregory S. Chirikjian is the Willis F. Harrington Professor and Department Chair at the University of Delaware's College of Engineering, Department of Mechanical Engineering. His expertise spans robotics, controls, computer vision, and applied mathematics. He is a Fellow of both IEEE and ASME. Education: PhD in Applied Mechanics, California Institute of Technology MSE in Mechanical Engineering, Johns Hopkins University BS in Engineering Mechanics, Johns Hopkins University BA in Mathematics, Johns Hopkins University Research Focus: Chirikjian's work integrates group theory with robotics, kinematics, and motion planning. Current projects include affordance-based reasoning for robotic systems, medical image registration, and the mechanics of macromolecules. His research explores both theoretical foundations and practical applications in robotics and engineering systems. Research Trends: Recent work emphasizes learning-free grasping techniques, uncertainty propagation in robotics, and deployable structures. His articles reflect interdisciplinary approaches combining mathematical rigor with practical robotic systems design. Awards: Fellow of the Institute of Electrical and Electronics Engineers (IEEE) Fellow of the American Society of Mechanical Engineers (ASME) Advising & Labs: Chirikjian leads the Spencer Lab, focusing on robotics and mathematical modeling. Though student names aren't listed here, his work involves graduate research in robotics systems and applied mathematics. Major grants support projects in soft robotics, sensorless manipulation, and robotic affordance learning. Future Directions: Ongoing work includes self-replicating robotic systems, probabilistic motion planning, and applications of non-Abelian Fourier analysis in engineering problems.

Fabrizio Sergiمشاهده پروفایل

دانشیار

• Biomechanical Engineering
• Robotics
• Neural Control of Movements
• +۴ مورد دیگر

Fabrizio Sergi is an Associate Professor in the Department of Mechanical Engineering at the University of Delaware, with joint appointments in the Biomedical Engineering Department and the Biomechanics and Movement Science Program. He leads the Human Robotics Lab and focuses on rehabilitation robotics, neural control of movements, and functional neuroimaging. Sergi holds a PhD, MS, and BS in Biomedical Engineering from Università Campus Bio-Medico di Roma. His research explores robotic tools to study motor control in healthy and post-stroke individuals, with a focus on MRI-compatible robots and functional magnetic resonance imaging (fMRI). He has secured grants from NIH, NSF, and AHA, including the NSF CAREER Award (2020) and AHA Scientist Development Grant (2017). His work includes developing protocols for studying brainstem contributions to motor responses and creating exoskeletons for gait assistance. Sergi’s research bridges robotics, biomechanics, and neuroscience, aiming to improve stroke recovery and neuromotor adaptation. His lab develops advanced technologies like Multi-Muscle Magnetic Resonance Elastography (MM-MRE) to non-invasively measure muscle forces and investigate neural substrates of motor control. He also studies adaptive control strategies for exoskeletons and the effects of torque assistance on walking mechanics. Key achievements include pioneering MRI-compatible robotic systems and identifying neural correlates of motor recovery. Current projects focus on optimizing robotic training protocols and understanding how proprioceptive feedback influences rehabilitation outcomes.

Guang-Jin Liمشاهده پروفایل

استاد

• Electrical Machines Design
• Renewable Energy Systems
• Electric Vehicles and Hybrid Technologies
• +۵ مورد دیگر

Professor Guang-Jin Li holds the position of Professor in Electrical Machines at the University of Sheffield's School of Electrical and Electronic Engineering. He leads the Electrical Machines and Drives Research Group, focusing on advanced electrical machine design for renewable energy and electric/hybrid vehicle applications. His research emphasizes fault tolerance, thermal management, and high-efficiency machine configurations. Education: BEng in Electrical Engineering, Wuhan University (2007) MSc in Electric Power Systems, Université de Paris XI (2008) PhD in Electrical Engineering, École Normale Supérieure de Cachan (2011) Research interests include novel permanent magnet machines, switched reluctance machines, fault diagnostics (e.g., inter-turn short-circuits), and thermal cooling strategies for offshore wind and EV applications. His work bridges academic innovation with industry collaboration, notably with Siemens-Gamesa and CRRC. Grants and Projects: EPSRC funding for advanced thermomagnetic cooling (2020–2022) Offshore Renewable Catapult grant for wind turbine powertrain research (2019–2027) Innovate UK projects on low-carbon vehicle inverters and power tool motors Labs/Teams: Active in the EPSRC Centre for Doctoral Training in Offshore Wind Energy and the Siemens Wind Power Prosperity Partnership. Supervises research in modular machines, ferrofluid cooling, and fault-tolerant designs.

Jim W. Portegiesمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Applied Mathematics
• +۵ مورد دیگر

Jim W. Portegies is an Assistant Professor in the Applied Analysis group at the Eindhoven University of Technology (TU/e). He holds additional roles as EAISI Foundational Assistant Professor and EAISI Mobility Assistant Professor within the TU/e's interdisciplinary initiatives. His research focuses on applying mathematical techniques from analysis, geometry, and measure theory to problems in machine learning and artificial intelligence, with a particular interest in designing algorithms that emulate human learning mechanisms. He obtained his MSc in Industrial and Applied Mathematics and Applied Physics from TU/e before completing his PhD in Mathematics at the Courant Institute of Mathematical Sciences, New York. After postdoctoral work at the Max Planck Institute in Leipzig, he returned to TU/e in 2016. Education: MSc in Industrial and Applied Mathematics & Applied Physics (TU/e, 2009) PhD in Mathematics (Courant Institute, NYU, 2014) Research Interests: Jim's work bridges pure mathematics and applied AI. Key areas include: Geometric and spectral methods for machine learning Universal learning algorithms inspired by human cognition Analysis of dimensionality reduction techniques Stochastic processes and control systems His recent work explores neural stochastic differential equations and interpretable AI mechanisms. Awards: Member of TU/e Young Academy of Engineering (2016–present) Collaborations & Grants: Jim collaborates extensively in interdisciplinary projects, including EU-funded initiatives on AI mobility systems. His research has been supported by grants from NWO (Netherlands Organization for Scientific Research) and industry partnerships with semiconductor and control systems companies. Labs & Teams: He contributes to the TU/e's Center for Analysis, Scientific Computing and Applications (CASA) and leads the Applied Analysis & AI research group, focusing on theoretical foundations of AI and their practical implementations.

Guillaume SANDOUمشاهده پروفایل

استاد

• Model Predictive Control
• Optimization
• Autonomous Systems
• +۹ مورد دیگر

Guillaume SANDOU is a Professor at CentraleSupélec, University Paris-Saclay, leading the Control Department and affiliated with the Signals and Systems Laboratory (L2S). He holds a Ph.D. (2005) and HDR (2012) from University Paris-Sud XI. His research focuses on optimization-based control methodologies, including model predictive control (MPC), metaheuristics, and energy systems. He has supervised numerous PhD students, contributing to advancements in autonomous systems, wind farm control, and smart grid technologies. Key research areas include robust control, multi-agent systems, and sensorless control for electric drives. He actively contributes to education, redesigning curricula to integrate modern control trends and industry needs, impacting over 800 students annually. His work spans applications in energy optimization, autonomous driving, and industrial automation. Publications emphasize innovative control strategies, with recent work on game-theoretic autonomous driving frameworks and energy management systems. He has secured patents in wind farm control and electric machine systems. Current and past students reflect his interdisciplinary approach, addressing both theoretical and applied challenges in control engineering.

Oleh Kiselychnykمشاهده پروفایل

دانشیار

• Power Electronics
• Renewable Energy Systems
• Electric Vehicle Technology
• +۳ مورد دیگر

Dr. Oleh Kiselychnyk is an Associate Professor in the School of Engineering at the University of Warwick, where he leads the Power and Control Systems Research Laboratory. He previously held roles as a Science City Research Fellow (2012–2015) and Assistant Professor (2015–2019). His expertise spans energy-efficient control systems, power electronics, and renewable energy integration. He coordinates the MSc Electrical Power Engineering program and teaches advanced modules on power electronic converters and drive control. Research interests focus on optimal control of electric vehicle drives, self-excited induction generators, and grid-integrated photovoltaic systems. Notable projects include EPSRC-funded initiatives on multilevel inverters, clean energy storage, and modular transportation architectures. He has supervised over 30 student projects on motor drives, power converters, and renewable energy applications. Key contributions include advancements in sensorless control algorithms for pumps/fans, neural network-based parameter estimation, and nonlinear control strategies for energy storage systems. His work bridges theoretical modeling with practical implementation in industrial and automotive sectors. Dr. Kiselychnyk collaborates with industry partners like Hyundai Motor Europe and AVL Powertrain, translating research into real-world applications. His lab facilities support experimental validation of novel control techniques and power electronic topologies.

Joachim Rudolphمشاهده پروفایل

استاد

• Control Theory
• Distributed Parameter Systems
• Robotics
• +۸ مورد دیگر

Prof. Joachim Rudolph is a full professor and head of the Chair of Systems Theory and Control Engineering at Saarland University, Germany. He holds a doctoral degree from Université Paris Sud (1991) and a habilitation from TU Dresden (2003). His research focuses on control theory, distributed parameter systems, robotics, and multicopter coordination. He leads projects on cooperative multicopter load transport with heavy ropes and digital hydraulics. Rudolph is an associate editor for multiple journals and a member of IEEE, IMA, and IFAC. Education: 1991: PhD, Université Paris Sud, France 2003: Habilitation, TU Dresden, Germany 1989: Dipl.-Ing., Stuttgart University, Germany Research Interests: Nonlinear control and model-based methods PDE-ODE coupled systems and hyperbolic PDEs Robotics and multicopter coordination Parameter identification and observer design His work on distributed parameter systems applies flatness-based control to systems like heavy ropes and fluid transmission lines. Recent projects include DFG-funded research on tricopter load transport and digital hydraulics. Teaching: Systems Theory and Control Engineering series (courses 1-5) System Modelling - Continuous Systems Advanced control topics for mechatronics Key Roles: Erasmus coordinator for Mechatronics Deputy Managing Director for Systems Engineering Editorial roles for Mathematical and Computer Modelling of Dynamical Systems and others Lab/Team: The Chair of Systems Theory and Control Engineering actively develops control algorithms for aerospace robotics, hydraulic systems, and industrial automation.

Laurent Gerbaudمشاهده پروفایل

استاد

• Computer Aided Design
• Modelling
• Dynamic simulation
• +۲ مورد دیگر

Laurent Gerbaud is a Professor at the ENS de Grenoble (Grenoble Institute of Technology) , affiliated with the G2Elab research laboratory and the MAGE team. His expertise lies in computer-aided design (CAD) of electrical systems, with a focus on electrical drives and power electronics. Research Interests: Analytical modeling, time/frequency simulation, gradient-based optimization, and CAD tool development. Teaching Activities: Computer-aided design, energy conversion, numerical methods, and optimization techniques. Research Trends across his publications highlight the application of advanced optimization methods (e.g., SQP, automatic differentiation) to complex electromagnetic and electrical systems, emphasizing electromagnetic compatibility (EMC) in aerospace, hybrid train energy management, and thermal modeling for multiphysics systems. His work bridges analytical modeling with practical implementation in renewable energy and transportation domains. Laboratory Affiliation : G2Elab (Grenoble Electrical Engineering Laboratory), located at Grenoble Cedex 1, France.

Zunaib Aliمشاهده پروفایل

مدرس ارشد

• Power Electronics Control
• Renewable Energy Systems
• Smart Grids
• +۴ مورد دیگر

Zunaib Ali is a Senior Lecturer in the Department of Electrical and Electronic Engineering at London South Bank University (LSBU). He contributes to the Innovate UK HAWKSBI project and has held roles at Queen Mary University of London and Northumbria University. His research focuses on power electronics control, renewable energy integration, and smart grid technologies, with expertise in MATLAB/Simulink, real-time simulators (dSPACE, Speedgoat), and machine learning for energy systems. He holds a B.Sc. in Electronic Engineering (2013) from UET Peshawar, an M.Sc. in Electrical Engineering (2015) from COMSATS University, and a Ph.D. in Electrical Engineering (2018) from Frederick University, Cyprus. His academic career includes teaching modules like Electrical Circuit Analysis and Power Electronics at LSBU. Research collaborations span institutions like Queen Mary University and industries such as Otaskies Energy Ltd. Dr. Ali leads multiple funded projects totaling over £750,000, including the £310,000 Smart Power Hub for Electrified Transport (2025–present) and Net Zero Futures initiatives (2021–2025). His work aligns with UN Sustainable Development Goals, emphasizing clean energy and sustainable cities. Research Interests: Design of power electronic converters for renewable integration Machine learning applications in energy systems Electric vehicle (EV) charging infrastructure Microgrid and nanogrid architectures Battery energy storage systems Vehicle-to-Grid (V2G) technology Grants & Collaborations: PI: £310k Smart Power Hub (Innovate UK) Co-I: £400k+ Net Zero Futures series (Greater London Authority) Collaborations with PBDesign EVJuiceNgo, Advanced Infrastructure Limited PAK-UK Education Gateway Mobility Partnership (British Council) His work emphasizes sustainable energy transitions and grid resilience, with publications spanning fault detection, renewable forecasting, and control system optimization. Labs/Teams: Active in Real-Time Power Laboratory (QMUL), Northumbria University’s microgrid pilot, and industry partnerships for EV and renewable tech demonstration.

• Power Electronics
• Renewable Energy Systems
• Battery Management Systems
• +۵ مورد دیگر

Tomi Roinila is an Associate Professor at the Department of Electrical Engineering, Faculty of Information Technology and Communication Sciences, Tampere University. His research focuses on power electronics, energy storage systems, and impedance-based analysis techniques for batteries and grid stability. He has contributed extensively to the design of high-efficiency DC-DC converters, battery management systems, and real-time monitoring technologies. His work emphasizes practical implementations of impedance measurement methods for lithium-ion batteries and grid-connected systems, addressing challenges in renewable energy integration, grid stability, and second-life battery applications. He has also explored hardware-in-the-loop (HIL) testing for power electronics systems and adaptive control strategies for inverters and STATCOM applications. Roinila's publications highlight advancements in converter topologies, battery health monitoring, and real-time stability assessment of multi-converter systems. His research bridges theoretical modeling with experimental validation, aiming to improve energy efficiency and system reliability in both academic and industrial contexts.

• Robotics
• Agricultural Robotics
• Adaptive Control Systems
• +۶ مورد دیگر

Antonio Candea Leite is an Associate Professor at the Department of Mechanical Engineering and Technology Management, Norwegian University of Life Sciences (NMBU). His research focuses on adaptive and robust control systems, visual servoing, robot manipulators, and agricultural robotics applications. His work emphasizes: Development of autonomous navigation systems for agricultural robots Integration of computer vision for precision agriculture tasks Control strategies for uncertain robotic systems Automation in food quality measurement and pest management Advanced sensor integration for manufacturing processes Recent research trends show strong emphasis on: CNN-based crop row detection for autonomous navigation (2024) Human-robot collaboration frameworks for fruit picking (2024) Robotics solutions for fatty acid measurement in food production (2023-2022) Precision pest control systems using smart automation (2023) No scientific awards or grants are explicitly listed in the provided information. He is actively involved in advising and developing robotic platforms for agricultural and industrial applications without specific student names mentioned here.