جست‌وجوی استاد و پژوهشگر

David S. Wackمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Biomedical Engineering
• Brain Research
• +۵ مورد دیگر

David S. Wack is an Associate Professor at the University at Buffalo's Jacobs School of Medicine & Biomedical Sciences, Department of Radiology. His research focuses on medical image analysis and neuroimaging, particularly in auditory processing and parameter estimation from PET, MRI, and CT images. He has held academic positions since 1992, progressing from instructor roles to his current rank. His work includes NIH-funded projects on imaging technologies and collaborations with institutions like Canon Medical Systems and UBNS. Education: PhD in Communicative Disorders and Sciences (SUNY Buffalo, 2010) MA in Applied Mathematics (SUNY Buffalo, 1992) BA in Applied Mathematics and Music Performance (SUNY Buffalo, 1989) Research Interests: Development of parametric maps from medical images Machine learning applications in neuroimaging Neuroimaging of auditory and language processing Dynamic image noise reduction and segmentation algorithms Neural markers of top-down compensation in speech processing Recent Projects: NIH-funded self-collimating SPECT breast tomography system 4D flow MRI for intracranial atherosclerotic disease assessment Machine learning for neuroimage classification Grants & Service: Member of Jacobs School faculty council and UB Faculty Student Association board Editorial roles at Frontiers in Neuroscience (Brain Imaging Methods, Decision Neuroscience) Labs & Teams: Buffalo Neuroimaging Analysis Center Collaborations with UBNS, Canon Medical, and VA Western New York Health Care System

• Power Electronics
• Electrical Machines
• Motor Drives
• +۵ مورد دیگر

Paolo Pescetto is a Fixed-term tenure-track Assistant Professor in the Department of Energy (DENERG) at Politecnico di Torino, where he is also a member of the Interdepartmental Center PEIC (Power Electronics Innovation Center). He serves on multiple academic boards including the College of Electrical and Energy Engineering, College of Computer, Film and Mechatronics Engineering, and College of Mechanical, Aerospace, and Automotive Engineering. His research focuses on power electronics, electrical machines, and motor drives with particular emphasis on electric vehicle applications. His work spans motor control strategies, thermal management of high-power density motors, sensorless control techniques, and integrated power systems for e-mobility. He has developed advanced methodologies for flux mapping, torque ripple compensation, and fault protection in permanent magnet and synchronous reluctance machines. Analysis of his recent publications reveals a strong trend toward solving practical challenges in electric vehicle powertrains, with significant contributions in multi-phase motor drives, thermal management, and fault-tolerant control systems. His work bridges theoretical advances with practical automotive applications, particularly in third-generation electric vehicle technologies. Dr. Pescetto holds multiple patents in motor control technologies, including methods for MTPA tracking without HF injection, spatial harmonic flux-map identification, and isolated on-board battery chargers for electric vehicles. His intellectual property demonstrates practical innovation in the field of motor drives and power electronics. He actively supervises PhD students Andrei Bojoi and Chen Chen in the Electrical, Electronics, and Communications Engineering program, focusing on electric motor drives and sustainable traction electrification. His research projects include commercial contracts on sensorless control of synchronous reluctance machines, firmware implementation for motor control, and advanced sensorless control methodologies for brushless motors. As a member of the PEEMD Research Group within DENERG, Dr. Pescetto contributes to cutting-edge research in power electronics and motor drives, with a strong industry collaboration focus that translates academic research into practical automotive solutions.

• Power Electronics
• Electric Drives
• Railway Electrification
• +۳ مورد دیگر

Paolo Pozzobon serves as an Associate Professor in the Department of Naval, Electrical, Electronic and Telecommunications Engineering (DITEN) at the University of Genoa. He teaches Power Electronics for Energy and Mobility and Software/Hardware Laboratory for Power Electronic Systems across undergraduate and graduate Electrical Engineering programs for academic years 2024-2025 and 2025-2026, demonstrating active engagement in electrical engineering education with specialization in power conversion systems. His research spans Power Electronics, Electric Drives, Railway Electrification, Energy Storage Systems, Power System Modelling, and Control Systems. Key investigations include multi-input bidirectional DC-DC converter topologies for hybrid energy storage, torque control algorithms for induction motor drives at low switching frequencies, and comprehensive modeling of 2x25 kV autotransformer railway systems. His work integrates optimization techniques like genetic algorithms for parameter estimation in traction networks and emphasizes practical validation through current measurements and transmission line modeling. Publication trends reveal sustained expertise in railway electrification systems (2006-2008) with recent pivoting toward energy storage and mobility applications. His 2024 works on multi-input converters and torque sub-harmonic reduction highlight current focus on efficiency optimization in power conversion for sustainable transportation, while earlier research established foundational contributions to railway power system modeling and parameter determination through innovative measurement and simulation approaches.

• Electrical Machines and Energy Conversion
• Control Theory and Applications
• Artificial Intelligence
• +۳ مورد دیگر

Hilmi AYGÜN is an Assistant Professor in the Department of Mechatronics Engineering at Karabük University's Faculty of Engineering and Natural Sciences, where he has been serving since 2019. His academic career began as a Research Assistant in the Electrical and Electronics Engineering Department from 2009-2019 before transitioning to his current position in Mechatronics Engineering. He also serves as the Erasmus Coordinator for both the Mechatronics Engineering Department and the university since 2021. Education: PhD in Electrical and Electronics Engineering (2011-2019), Karabük University, Institute of Science MSc in Electrical and Electronics Engineering (2010-2011), Karabük University, Institute of Science BSc in Electrical and Electronics Engineering (2003-2007), Kırıkkale University, Faculty of Engineering Hilmi AYGÜN's research primarily focuses on electrical machines and energy conversion systems, with particular emphasis on motor control algorithms for electric vehicle applications. His work integrates control theory with artificial intelligence techniques, especially optimization algorithms like Particle Swarm Optimization (PSO) and the Yusufcuk Algorithm. He has made significant contributions to field-oriented control of induction motors, DC motor control systems, and wind energy applications. His publication record shows a clear trajectory toward increasingly sophisticated control systems for electromechanical applications, with recent work focusing on metaheuristic methods for motor control, optimization of wind energy systems, and advanced DC motor control techniques. His research bridges theoretical control concepts with practical engineering applications, particularly in transportation and renewable energy sectors. Hilmi AYGÜN has successfully advised at least one Master's student, Hersh Hasan Taha Al Dawoodı, whose thesis focused on field-oriented control of induction motors using metaheuristic methods. He has participated in two major research projects: one on optimal flux reference direct torque control for asynchronous motors used in electric vehicles (2015-2019), and another on controlling bed temperature in fluidized bed boilers using PSO-PID controllers (2011-2013). As an educator, he has taught numerous courses including Electric Machine Dynamics, Modeling and Control of Biomedical Systems, Control of Electric Machines, Electric and Hybrid Vehicles, Industrial Automation, and various electronics courses. His teaching spans both undergraduate and graduate levels, demonstrating his versatility across multiple engineering disciplines within the mechatronics field.

• Control Systems
• Robotics
• Mathematical Modelling
• +۸ مورد دیگر

Claudio Gaz is a Senior Lecturer in Mechatronics, Control, and Autonomous Systems at the Department of Mechanical Engineering, Faculty of Engineering, Computing and the Environment, Kingston University London. He holds a PhD in Automation and Operational Research (2016) and a Master's in Control Engineering with top marks (2011) from Sapienza Università di Roma, and was awarded the French national qualification as maître de conférences (class 61) in 2019. His research spans control systems, robotics, and mathematical modeling, with a focus on industrial manipulators (e.g., KUKA LWR, Universal Robots UR10) and biological processes like glucose homeostasis. Recent work involves dynamic parameter identification for collaborative robots and sensorless force feedback in medical robotics. He has collaborated with institutions such as Sapienza Università di Roma, CNR-IASI (Italian National Research Council), and Airbus Group. His scientific awards include: Fellowship of the Higher Education Academy (FHEA) . Gaz has contributed to journals and conferences in robotics, control theory, and biomedical modeling, with a strong emphasis on real-time adaptive algorithms and safety in physical human-robot interaction.

Niko Nevarantaمشاهده پروفایل

دانشیار

• Electrical and Electronic Engineering
• Control and Systems Engineering
• Modelling and Simulation
• +۶ مورد دیگر

Niko Nevaranta serves as an Associate Professor (Tenure Track) in the Department of Electrical Engineering at Lappeenranta-Lahti University of Technology (LUT), specifically within the School of Energy Systems. His academic journey began at LUT where he earned his B.Sc. (2010), M.Sc. (2011), and D.Sc. (2016) degrees in electrical engineering. His career path includes a visiting researcher position at KTH Royal Institute of Technology in Stockholm (2018) and a post-doctoral researcher role funded by the Academy of Finland (2019-2022). Nevaranta's research focuses on data-driven modeling and control systems for electromechanical and energy applications. His primary expertise lies in Industrial Informatics for Energy System Disruption, with specific interests in high-speed rotating machinery, system identification, parameter estimation, and intelligent control systems. His work bridges theoretical control engineering with practical industrial applications, particularly in the energy transition sector. Analysis of his recent publications reveals a strong emphasis on active magnetic bearing technology, rotor dynamics, and high-speed machinery applications. His research increasingly incorporates data-driven approaches and machine learning techniques to address complex control challenges in energy systems. The publications demonstrate a clear progression from fundamental control theory toward practical implementation in real-world energy conversion systems. As an educator, Nevaranta has developed innovative teaching materials for control engineering, including MATLAB-based tools and virtual learning environments. His educational contributions focus on making complex control concepts accessible to undergraduate students through interactive and visual learning approaches. Nevaranta works within the laboratory of Control Engineering and Digital Systems at LUT, where he leads research on advanced control methodologies for energy systems. His current projects involve high-speed machine technology, particularly in applications related to biomass and waste heat recovery, as well as emerging technologies in direct air capture systems.

• Public Transportation Electrification
• Electric Vehicle Drive Control
• Battery Degradation Modeling
• +۴ مورد دیگر

Dr. Syed M Nawazish Ali is a Research Fellow at RMIT University’s School of Engineering (City Campus, Australia) since July 2022. He has held academic roles at Macquarie University (Casual Academic, 2018–2020) and Aalborg University (Visiting Research Fellow, 2019–2020). His industry experience includes roles at Evenergi Pty Ltd and Magnetica Limited in Australia. Education: B.Sc. in Electrical Engineering, University of Engineering & Technology, Lahore (2013) M.Sc. in Electrical Engineering, COMSATS University, Lahore (2016) Ph.D. in Electrical Engineering, Macquarie University, Sydney (2022) Research Interests: Dr. Ali specializes in data analysis of public transportation electrification, electric vehicle (EV) drive control, battery degradation studies, optimization algorithms for battery health estimation, and grid impact of EV penetration. His work addresses thermal degradation in EV motor drives, fault-tolerant inverter designs, and sustainable integration of renewable energy with transport systems. Article Trends: His recent publications focus on harmonizing EV charging with smart grids, optimizing energy control via Machine Learning and genetic algorithms, and enhancing fault tolerance in power electronics. Key themes include thermal management of motor drives, multi-energy system integration, and decentralized energy trading models. Scientific Awards: Postgraduate Research Fund grant and DVC Research Commendation, Macquarie University (2020) 1st position in oral research presentation at Macquarie University’s Higher Degree Research Conference (2019) International Research Training Program Scholarship (Commonwealth Government-funded) for Ph.D. (2017) Prime Minister’s Laptop Scheme award (2016) Top of FA14-MSEE batch at COMSATS University (2016) KAKEZAI Scholarship at UET Lahore (2011–2013) Supervision & Grants: Available for Masters/PhD supervision in EV control systems. Secured grants including the Commonwealth Government’s International Research Training Program Scholarship and Macquarie University’s Postgraduate Research Fund. Key projects: C4NET Project 66 (Zero Emission Bus Trial) and EV battery degradation control research.

Prasad Enjetiمشاهده پروفایل

استاد

• Power Electronics
• Renewable Energy Systems
• Smart Grid Technologies
• +۳ مورد دیگر

Prasad Enjeti is a Professor and Texas Instruments Jack Kilby Chair in Electrical & Computer Engineering at Texas A&M University, College of Engineering. With expertise in power electronics and renewable energy systems, he has significantly advanced grid-connected technologies, energy storage, and power quality solutions. Ph.D., Electrical Engineering, Concordia University (1988) M.S., Electrical Engineering, I.I.T. Kanpur (1982) B.S., Electrical Engineering, Osmania University (1980) His research focuses on power electronic converters for renewable energy integration, solid-state transformers, high-temperature power systems, grid-edge intelligence, and cybersecurity in distributed energy systems. He has pioneered innovations in AC/DC microgrids, droop control, and advanced filtering technologies. Recent publications emphasize cybersecurity for renewable systems, wide-bandgap semiconductor applications, and AI-driven power electronics optimization. He holds 20+ patents and has supervised 29 Ph.D. and over 50 Master's students, many now in leading academic and industrial positions. IEEE Fellow (2000) R. David Middlebrook Technical Achievement Award (2012) Best Paper Awards at PCIM (2014), IEEE IAS IPCC (2003, 2002, 1998, 1996) NSF Research Initiation Award (1990) Texas A&M Faculty Fellow (1996-97, 2001) He leads the Power Electronics Intelligence at the Network Edge (PINE) research group, with significant contributions to eVTOL energy systems, cryptocurrency mining load analysis, and secure peer-to-peer energy transactions.

Chris Braceمشاهده پروفایل

استاد

• Automotive Engineering
• Powertrain Systems
• Internal Combustion Engines
• +۵ مورد دیگر

Chris Brace is a Professor of Automotive Propulsion and Deputy Director of the Powertrain Vehicle Research Centre at the University of Bath. His work focuses on advanced measurement, analysis, and control of multi-cylinder engine systems under dynamic conditions, with extensive collaboration with industry leaders like Ford Motor Company and Jaguar LandRover. He contributes to the United Nations Sustainable Development Goals (SDGs), particularly in sustainable mobility and low-emission propulsion systems. Education : Sandwich degree at University of Bath (1990), PhD (1996). Research interests encompass powertrain systems , internal combustion engines , hybrid electric vehicles , battery technology , and low-emission propulsion . His projects integrate nonlinear control systems, fault-tolerant designs, and data-driven validation architectures. Recent publications highlight advancements in emission control algorithms, adaptive critic networks for rotary engines, fault-tolerant motor control, and battery parameter modeling. These works reflect trends in automotive electrification , hybrid systems , and environmental sustainability . Supervision : Supervised PhD research on hybrid electric vehicle control strategies (Christopher Vagg, 2015). Grants & Projects include Innovate UK-funded initiatives like Battery Integrated Wing (2025–2028) and EPSRC-supported JLR Prosperity Partnership (2021–2026). He also leads the IAAPS Institute for Advanced Automotive Propulsion Systems. Key Collaborations : Ford Motor Company, Jaguar LandRover, West of England Combined Authority.

Bob Kirschمشاهده پروفایل

استاد

• Brain-Computer Interfaces
• Functional Electrical Stimulation
• Neuroprosthetics
• +۳ مورد دیگر

Bob Kirsch serves as Professor and Department Chair of Biomedical Engineering at Case Western Reserve University, where he also directs the Cleveland FES Center. His research focuses on restoring motor function for paralyzed individuals through neural engineering innovations in brain-computer interfaces and functional electrical stimulation systems. His educational background includes: Ph.D. in Biomedical Engineering from Northwestern University M.S. in Biomedical Engineering from Northwestern University (1986) B.S. in Electrical Engineering from the University of Cincinnati (1982) Dr. Kirsch's research spans intracortical brain-computer interfaces for movement restoration, neural decoding algorithms for grasp force and speech, and functional electrical stimulation integration with BCI systems. His work emphasizes closed-loop control architectures , artifact reduction in neural recordings , and reinforcement learning approaches for neuroprosthetic control, targeting clinical translation for tetraplegia rehabilitation. Analysis of his 2016-2020 publications reveals consistent focus on improving BCI calibration speed, enhancing movement decoding accuracy, and developing robust systems for real-world use. Key trends include leveraging human-generated rewards for controller training, addressing signal-independent noise limitations, and creating hybrid approaches combining cortical recordings with FES for functional movement restoration. His recognition includes: Faculty Distinguished Research Award from Case Western Reserve University (2023) As Department Chair and Cleveland FES Center Director, Dr. Kirsch leads multidisciplinary teams developing next-generation neuroprosthetics. His research program, supported by NIH and NSF grants, trains graduate students in neural engineering while advancing clinical applications through the BrainGate consortium collaboration. Current efforts focus on improving BCI communication rates and expanding movement restoration capabilities for paralyzed individuals. The Cleveland FES Center under his direction serves as a hub for neuroprosthetics innovation, integrating expertise in neural signal processing, biomechanics, and clinical rehabilitation to develop practical solutions for restoring lost motor function through implanted and non-invasive technologies.

• Control Systems
• Machine Learning
• Electrical Engineering
• +۴ مورد دیگر

Marko Tanasković (born December 6, 1986) is a researcher at Singidunum University with a PhD in Information Technology and Electrical Engineering from ETH Zurich (2015). His academic background includes master's (ETH Zurich, 2011) and bachelor's (University of Belgrade, 2009) studies in Electrical Engineering. Doctoral studies: Information Technology and Electrical Engineering, ETH Zurich (2011-2015) Master studies: Information Technology and Electrical Engineering, ETH Zurich (2009-2011) Basic studies: Electrical Engineering, University of Belgrade (2005-2009) Tanasković's research focuses on control systems , predictive modeling , and optimization algorithms for mechanical and electrical systems. His work addresses adaptive model predictive control (MPC), sensorless motor positioning, and data-driven approaches for nonlinear systems. Recent publications (2018-2024) demonstrate expertise in: Embedded control systems (rotor polarity detection) Drone forensics and autonomous navigation Industrial automation (LabVIEW applications) Biomedical sensor development ('Smart Anklet') Machine learning optimization (firefly algorithm)

• Biomechanics
• Musculoskeletal System
• Human Movement Analysis
• +۳ مورد دیگر

Maarten Afschrift is an Assistant Professor at the Vrije Universiteit Amsterdam, affiliated with the Faculty of Behavioural and Movement Sciences, Department of Biomechanics. He holds additional roles at IBBA and AMS - Rehabilitation & Development. His research focuses on biomechanical modeling of human movement, particularly in musculoskeletal systems and gait analysis. He specializes in predictive simulations of locomotion, exoskeleton assistance, and the biomechanical implications of aging on movement strategies. Research Interests: Biomechanics of human movement and gait Musculoskeletal modeling and simulation Exoskeleton and assistive technology design Effects of aging on motor control and balance Predictive control strategies in human locomotion Recent Research Trends: His work emphasizes optimizing exoskeleton assistance for lower limbs, understanding metabolic energetics during walking, and modeling foot mechanics to improve gait simulations. Recent studies explore trade-offs between accuracy, speed, and stability in stepping tasks across age groups, leveraging computational frameworks like PredSim for predictive analysis. Teaching & Grants: He teaches courses on biomechanics of locomotion and contributes to editorial work in biomechanical journals. No specific grants or awards are listed, but his research is supported through institutional and collaborative projects. Labs/Teams: Active in interdisciplinary teams at IBBA and AMS, focusing on rehabilitation engineering and biomechanical innovations.

Naeem Mianمشاهده پروفایل

استاد

• Machine Tools
• Thermal Engineering
• Sensor Technology
• +۷ مورد دیگر

Dr. Naeem Mian is a Professor and Subject Area Leader in Mechanical and Automotive Engineering at the School of Computing and Engineering, University of Huddersfield. He holds a BEng in Electronic Engineering, MSc in Engineering Control Systems and Instrumentation, and a PhD in Machine Tools Thermal Finite Element Analysis (FEA). His research focuses on thermal behavior of machine tools, vibration sensors, control engineering, and sustainable technologies. He is affiliated with the Centre for Precision Technologies and the Centre for Thermofluids, Energy Systems, and High-Performance Computing. Dr. Mian’s research explores thermal error mitigation, sensor calibration, and advanced manufacturing systems. His work contributes to UN Sustainable Development Goals via innovations in energy-efficient systems and smart materials. Recent projects include developing a 'Smart Mattress' to reduce landfill waste and improve sleep quality. His publications span thermal modeling, hybrid generators, and wearable e-textiles. Notable collaborations involve wind energy optimization, bioaerosol dispersion analysis in railways, and precision vibration sensing. He actively supervises PhD students and participates in interdisciplinary projects combining mechanical, electrical, and materials engineering.

Behrooz Bahraniمشاهده پروفایل

استاد

• Power Electronics
• Grid Integration of Renewable Energy
• Inverter-Based Resources (IBRs)
• +۴ مورد دیگر

Professor Behrooz Bahrani is a faculty member in the Department of Electrical and Computer Systems Engineering at Monash University, leading the Grid Innovation Hub. His research focuses on integrating renewable energy into power grids, addressing challenges posed by high penetration of inverter-based resources (IBRs). He holds a PhD from EPFL (Switzerland) and has held postdoctoral positions at global institutions. His expertise includes power electronics control, grid stability, and electric vehicles. Education: B.Sc. (Electrical Engineering, Sharif University of Technology), M.Sc. (University of Toronto), PhD (EPFL). Awards include Swiss National Science Foundation Postdoc.Mobility Fellowships (2013–2014). Research emphasizes mitigating climate change through renewable energy integration, with projects on grid-forming inverters, system strength assessment, and synchronous condenser planning. Collaborations with industry (e.g., AEMO) ensure practical impact. He actively teaches and mentors postgraduate students, fostering next-generation engineers in power systems innovation. Labs/Teams: Director of Monash’s Grid Innovation Hub, collaborating on global initiatives like the EPICS project for carbon-free energy systems. Current projects include electrolyser technology for grid stability and power system transformation research.

• Automotive Engineering
• Railway Engineering
• Mechanical Engineering
• +۶ مورد دیگر

Vicente Díaz López is a Full Professor in the Department of Mechanical Engineering at Carlos III University of Madrid. He serves as Director of the Duque de Santomaró Institute of Motor Vehicle Safety and Director of the Master's Degree in Railway Engineering. Academic Department: Mechanical Engineering Research Group: Experimental Mechanics, Calculations and Transport Group (MECATRAN) Contact: vdiaz@uc3m.es Research Interests span automotive and railway engineering, focusing on: Intelligent tire systems for grip and friction estimation Vehicular dynamics and stability control Braking efficiency and safety analysis Structural mechanics in transport systems Sensor fusion and neural networks for vehicle parameter estimation Roadworthiness testing methodologies Recent Publications demonstrate expertise in: Brake force estimation techniques Intelligent tire development Vehicle roll stability control Structural failure analysis in transport Low-cost sensor systems for driver monitoring Projects include: Principal investigator of the fBrake software suite (2014–present) for braking efficiency analysis Multiple contracts with technical inspection agencies (ITV) and companies like Bombardier Patent development for driving style evaluation systems