Computational Wind Engineering Professors and Supervisors | ApplySharif

جست‌وجوی استاد و پژوهشگر

استاد راهنما، استاد دانشگاه یا پژوهشگر مناسب برای مسیر پژوهشی‌تان را پیدا کنید و با او ارتباط بگیرید.

نمایش ۷۳۶-۷۵۰ از ۳٬۷۱۷ استاد راهنما

اطلاعات این پروفایل‌ها از صفحات عمومی دانشگاه‌ها جمع‌آوری شده و ممکن است به‌روز نباشد.

Veit Dominik Kunzمشاهده پروفایل

استاد

Hamburg University of Applied SciencesGermany

Prof. Veit Dominik Kunz is a Professor of Electrical Engineering and Renewable Energy at the Department of Process Engineering, Hamburg University of Applied Sciences. His academic role includes teaching and research in advanced electrical systems, power electronics, and renewable energy technologies. He is affiliated with the Faculty of Engineering and Computer Science and leads research projects such as FLEDERWIND (focusing on bat detection in wind parks) and Drones4Bats (wildlife impact assessment). His expertise spans semiconductor device design, nanotechnology, and strategic product development. Research interests include optimizing renewable energy systems, mitigating environmental impacts of wind energy, and advancing semiconductor technologies for high-performance electronics. His work bridges academic research with practical applications, particularly in energy management and sustainable technologies. Publications highlight contributions to vertical MOSFET design, renewable energy systems, and product development strategies. He is also involved in academic governance as head of the examination committee for his department.

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Sukumar Kamalasadanمشاهده پروفایل

استاد

University of North Carolina at CharlotteUnited States

Dr. Sukumar Kamalasadan is a Professor and ECE Research Coordinator at the W.S. Lee College of Engineering, University of North Carolina at Charlotte. He holds a Ph.D. from the University of Toledo (2004), M.Eng. from Asian Institute of Technology (1999), and B.Tech. from University of Calicut (1991). His primary research focuses on smart grid design, renewable energy integration, power grid modernization, and real-time control systems. He has also been honored as a W.S. Lee College of Engineering Distinguished Scholar. Key research areas include microgrid management, optimal power flow (OPF) methodologies, inverter control technologies, and grid resilience strategies. His work addresses challenges such as distributed energy resource (DER) integration, voltage/frequency control in microgrids, and dynamic stability enhancement through advanced control architectures. Publications highlight innovations in OPF modeling (e.g., SOCP-based approaches), grid-forming/following inverter designs, and fault evaluation in active distribution networks. He has contributed to curricular updates in power engineering education, emphasizing situative pedagogy and concept map assessments. Grants and collaborations involve projects on decentralized grid operation, ancillary services via uninterruptible power supplies, and resilience evaluation of distribution systems against extreme weather events.

پروفایل رسمی دانشگاه

Udo Bachhieslمشاهده پروفایل

دانشیار

Graz University of TechnologyAustria

Udo Bachhiesl is an Associate Professor and Deputy Head of the Institute of Electricity Economics and Energy Innovation at Graz University of Technology. With a background in energy economics, he has established himself as an expert in energy and electricity economics, renewable energies, and energy innovation. His research focuses on energy transition modeling, power system economics, and renewable energy integration. Bachhiesl has contributed significantly to understanding the challenges of integrating renewables into electricity markets and developing modeling frameworks for energy system optimization. His work spans regional (particularly Styrian and Austrian), European, and international contexts including Africa and the Indian subcontinent. Bachhiesl's recent publications reveal a strong focus on hydrogen integration, energy system optimization models (including LEGO and ATLANTIS), and regional energy transition pathways. His work combines technical power system analysis with economic modeling to provide comprehensive insights into energy transitions. Klimaschutzpreis 2003 der Österreichischen Bundesregierung Young Scientist Best Paper Award 2003 As Deputy Head of the Institute, Bachhiesl oversees numerous research projects including UrbanHP (heat pump integration), iKlimET (climate and energy system models), and the Styria Energy Report series. His work connects academic research with practical energy policy implementation, particularly in the Styrian region of Austria. He has also contributed to the Energy Innovation Symposium series at TU Graz and maintains the ATLANTIS simulation model for European electricity systems.

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Apurva Narayanمشاهده پروفایل

استاد مدعو

University of British ColumbiaCanada

Dr. Apurva Narayan is an Affiliate Professor in Computer Science and Data Science, and an Associate Member in Mechanical Engineering at the University of British Columbia's Irving K. Barber Faculty of Science. His research focuses on artificial intelligence, machine learning (particularly explainable AI and quantum ML), data mining, cybersecurity of cyber-physical systems, and decision-making under uncertainty. He holds a PhD from the University of Waterloo (Systems Design Engineering) and a Bachelor's in Electrical Engineering from Dayalbagh Educational Institute. Education: PhD in Systems Design Engineering, University of Waterloo (2015) Bachelor of Engineering in Electrical Engineering, Dayalbagh Educational Institute (2008) Research Interests: Explainable AI/ML and quantum machine learning Data analytics and mining Safety/security of cyber-physical systems Graph-theoretic analysis of complex systems Decision-making under uncertainty Reverse engineering complex software systems Awards: Systems Society of India Young Scientist Award (under 40) MITACS Accelerate Award (2013) Dr. T.E. Unny Memorial Award (2011) Multiple teaching nominations at University of Waterloo Advising & Grants: Supervises graduate students in AI/ML and cybersecurity. Secured grants including MITACS Accelerate and Waterloo scholarships. Active in patent filings related to timed regular expressions. Labs/Teams: Engaged in collaborations within the UBC Department of Computer Science and cross-disciplinary projects with Mechanical Engineering on system reliability and quantum computing applications.

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Peter Gorm Larsenمشاهده پروفایل

استاد

Aarhus UniversityDenmark

Peter Gorm Larsen is Professor in the Department of Electrical and Computer Engineering at Aarhus University, affiliated with the DIGIT Center. With over 300 research outputs since 1989, his work centers on digital twins, cyber-physical systems, and embedded AI. Current projects include RoboSAPIENS (robotic adaptation), CP-SENS (cyber-physical sensing), and DIGIT-BENCH (digital twins for wind industry test benches). Research focuses on developing reusable digital twin platforms and autonomous reconfiguration frameworks. Recent publications demonstrate advancements in semantic interoperability for coupled digital twins and service-oriented architectures. Since 2018, Professor Larsen has received international recognition including the Reviewer Recognition award. His work spans robotics, sustainable energy systems, and healthcare applications. Professor Larsen maintains active collaborations across Europe and serves on multiple program committees. Teaching activities include Discrete Mathematics and supervision of graduate students in software engineering and embedded systems.

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Hugues MOUNIERمشاهده پروفایل

استاد

CentraleSupélecFrance

Professor Hugues MOUNIER is affiliated with Paris Saclay University and the Laboratoire des Signaux et Systèmes (L2S) at CentraleSupélec. His primary role is as a Professor leading the COMEDY team, focusing on control systems and their applications. He has been a permanent member of L2S since 2010 and joined Paris Saclay University in 2008. His research spans theoretical and applied domains: differential flatness (for nonlinear and infinite-dimensional systems), Liouvillian systems, controllability/observability properties, and applications in contemplative neuroscience, physiological systems, and engineering systems like drilling, automotive, and network control. He leads the ANR project MindMadeClear, integrating mathematical models for meditation practices with physiological and phenomenological analysis. Key contributions include modeling oilwell drilling vibrations, model-free control strategies for vehicles and data centers, and neuroscientific studies using EEG classification for meditation states. His work bridges abstract theory (e.g., flatness analysis for HPA axes) with real-world applications (e.g., congestion control, energy management). He collaborates internationally, presenting at venues like ECC, IFAC, and IEEE conferences. His lab teams include SYCOMORE and MODESTY, focusing on dynamical systems modeling and estimation. No awards are explicitly listed, but his extensive peer-reviewed publications reflect sustained academic impact.

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Juliette Chabassierمشاهده پروفایل

پژوهشگر

InriaFrance

Juliette Chabassier is a Researcher at the MAGIQUE-3D project team within Inria Bordeaux Sud-Ouest and affiliated with Université de Pau et des Pays de l'Adour . She holds a Ph.D. in Applied Mathematics from École Polytechnique (2012), advised by Patrick Joly and Antoine Chaigne. Roles: Junior Research Scientist (since 2013), Post-Doc at University of Pau (2012-2013) Research Focus: Acoustics of musical instruments, wave propagation modeling, numerical simulation of piano and wind instruments, energy-preserving discretization schemes, and viscothermal effects in ducts. Her work emphasizes physical modeling and computational acoustics , particularly in piano acoustics, wind instrument design, and heritage instrument digitization. She develops tools like OpenWind for simulating instrument responses and collaborates on projects involving piano soundboard analysis and historical instrument reconstruction. Her recent articles explore topics such as: Simulation of brass instruments using finite element models Thermoviscous effects in conical tubes Energy-conserving discretization for nonlinear wave equations Digital twins for heritage instruments like Besson trumpets She advises doctoral students including Elvira Shishenina and Izar Azpiroz , focusing on applied mathematics and acoustics. Her contributions include advanced numerical methods for acoustic-elastic coupling and boundary layer phenomena in exponential media. Current projects involve homogenization techniques for porous materials, real-time instrument simulation tools, and interdisciplinary work on acoustics education through open-source software.

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Riccardo Felicettiمشاهده پروفایل

پژوهشگر ارشد

Marche Polytechnic UniversityItaly

Riccardo Felicetti is a Research Fellow at the Department of Information Engineering, Università Politecnica delle Marche, within the Faculty of Engineering. He holds a Master's Degree (cum laude) in Computer and Automation Engineering (2016) and a Ph.D. (cum laude) in Information Engineering (2021) from the same university, with a thesis on “Active fault tolerant control for overactuated unmanned vehicles.” He also serves as Senior Tutor, coordinating tutor activities in the Faculty of Engineering. His research focuses on fault detection and diagnosis, fault-tolerant control, and optimization, with applications to unmanned vehicles (e.g., drones, ROVs) and energy management systems. He has contributed to advancements in systems like actuator fault tolerance, vibration-based fault detection, and energy optimization in smart grids. Key technical areas include disturbance observer-based control, adaptive Kalman filtering, and machine learning integration for system identification. His work bridges theoretical control frameworks with practical implementations in aerospace and marine robotics.

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JÓZSA Jánosمشاهده پروفایل

استاد

Budapest University of Technology and EconomicsHungary

JÓZSA János is a Professor at the Department of Hydraulic and Water Resources Engineering, Faculty of Civil Engineering, Budapest University of Technology and Economics. He serves as Coordinator of the Specialization in Infrastructure Engineering (MSc) and is a member of both the Pál Vásárhelyi Doctoral School of Civil Engineering and Earth Sciences and the Faculty's Habilitation and Doctoral Council. His research focuses on: Hydrodynamics of surface waters and interface processes Wind-induced lake currents and sediment motion Flow, mixing, and sediment transport in compound-channel rivers Floodplain inundation modeling Effects of ship-induced waves on river banks Analysis of his 2019-2024 publications reveals consistent emphasis on Danube River hydrodynamics, sediment transport mechanisms, and environmental impacts of engineering interventions. Key methodological contributions include validation of 2D/3D numerical models against field measurements, novel sediment transport calculation methods using shear Reynolds number, and practical frameworks for assessing ship wave impacts. His work bridges computational fluid dynamics with environmental monitoring. Professor Józsa has participated in international collaborations including the ERDF-funded SEDDON project for Austrian-Hungarian sediment research. No information on specific research grants or student advising was provided in the source materials.

پروفایل رسمی دانشگاه

Wayne W. Weaverمشاهده پروفایل

استاد

Michigan Technological UniversityUnited States

Wayne W. Weaver is a Professor of Mechanical and Aerospace Engineering at Michigan Technological University (MTU), serving as Associate Chair and Director of Graduate Studies. He also holds an affiliation as a Professor in the Electrical and Computer Engineering department. Weaver earned dual BS degrees in Electrical and Mechanical Engineering from GMI Engineering & Management Institute (1997), followed by MS and PhD in Electrical Engineering from the University of Illinois at Urbana-Champaign. His research focuses on power electronics, electric vehicle systems, nonlinear control strategies, and microgrid technologies, with particular emphasis on renewable energy integration and grid resilience. His professional experience includes roles at Caterpillar Inc. (1997-2003) and the US Army Corps of Engineers ERDC (2006-2008). He is a registered professional engineer in Illinois. Key research areas include microgrid stabilization, optimal control of energy systems, and wave energy converter optimization. Weaver has contributed to advancements in distributed energy resources, pulsed-power load management, and exergy-based control methodologies. Teaching responsibilities include courses on hybrid electric vehicle propulsion and linear systems theory. His work often bridges theoretical control frameworks with practical applications in maritime, military, and aerospace systems. Despite the lack of listed awards, his extensive publication record reflects impactful contributions to energy systems research. He collaborates with labs focused on renewable energy integration and resilient power grid architectures.

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Miroslaw Pawlakمشاهده پروفایل

استاد

University of ManitobaCanada

Dr. Miroslaw Pawlak is a Professor in the Department of Electrical and Computer Engineering at the University of Manitoba’s Price Faculty of Engineering. He holds a Ph.D. and D.Sc. in Computer Engineering from Wrocław University of Technology, Poland. As a Professional Engineer registered in Manitoba, he has held visiting positions at multiple institutions worldwide, including the University of Ulm and University of Göttingen as an Alexander von Humboldt Foundation Fellow. His research focuses on statistical signal processing, machine learning, nonparametric modeling, and system identification. He authored/co-authored influential books like Nonparametric System Identification (Cambridge University Press, 2010) and over 100 peer-reviewed publications. Dr. Pawlak has served as an Associate Editor for journals such as Pattern Recognition and IEEE Transactions on Information Theory , and was recognized in Stanford University’s World’s Top 2% Scientists list. Education: 1985: Ph.D. in Computer Engineering, Wrocław University of Technology 1999: D.Sc. in Computer Engineering, Wrocław University of Technology Research Interests: Dr. Pawlak specializes in advanced signal processing techniques, including nonparametric system identification, statistical analysis of stochastic signals, and machine learning applications in engineering systems. His work bridges theoretical foundations (e.g., operator theory with Hermite polynomials) and practical implementations (e.g., wind farm modeling and power system stability prediction). Publications: His recent work emphasizes nonparametric methods for system testing (e.g., Hammerstein systems) and interdisciplinary applications like power grid oscillation prediction using LASSO algorithms. He frequently collaborates with international researchers to advance signal processing theory and energy systems modeling. Awards: World’s Top 2% Scientists (Stanford University, 2021/2022) Professional Contributions: Dr. Pawlak’s editorial roles and visiting fellowships demonstrate his global influence. He has advised numerous graduate students and contributed to key textbooks shaping the field of system identification.

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Yuejian Chenمشاهده پروفایل

استادیار

University of ManitobaCanada

Dr. Yuejian Chen is an Assistant Professor in the Department of Mechanical Engineering at the University of Manitoba's Price Faculty of Engineering. His research focuses on dynamic modelling, vibration signal processing, artificial intelligence, and prognosis/health management for complex systems like railway vehicles, wind turbines, and steam turbines. He holds a PhD from the University of Alberta (2020) and was a postdoctoral fellow there until 2021. Prior to joining the University of Manitoba in 2024, he served as an Assistant Professor at Tongji University's Institute of Rail Transit in China from 2021 to 2024. His research integrates digital twins and advanced health management methodologies to ensure safe and cost-effective operation of mechanical systems. Key areas include non-stationary vibration analysis, fault detection via AI (e.g., LSTM networks), and physics-informed machine learning. He has authored/co-authored over 60 publications and serves on editorial boards for journals such as IEEE Sensors Journal , IEEE Transactions on Instrumentation and Measurement , and Smart and Resilient Transportation . Dr. Chen's work bridges theoretical advancements with practical applications, emphasizing railway transportation and energy systems. His recent publications (2021–2025) highlight contributions to gearbox fault detection under variable speed conditions, multi-camera metro monitoring systems, and data-driven load identification strategies. His research trends emphasize fusion of physical principles with AI for robust diagnostics and health management across mechanical systems. He is actively recruiting graduate students interested in dynamic systems, signal processing, and AI applications in mechanical engineering. His research group collaborates with industry partners to address real-world challenges in machinery safety and efficiency.

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Dušan Gordićمشاهده پروفایل

استاد

University of KragujevacSerbia

Dušan Gordić is a Professor in the Department of Energy and Process Engineering at the Faculty of Engineering, University of Kragujevac. His research focuses on energy efficiency, waste heat utilization, and sustainable industrial processes, with a particular emphasis on public infrastructure and food production systems. He holds a professorial position since 2012 and contributes to academic leadership through his chair in energy systems. His research interests span energy engineering, environmental impact assessment, and emerging technologies like AI-driven energy management. He has conducted case studies on kindergarten energy performance, industrial decarbonization, and 3D printing applications in education. His work integrates both theoretical and applied approaches, addressing challenges in renewable energy adoption and public building optimization. Key research themes: Energy systems, HVAC efficiency, sustainable manufacturing, and waste-to-energy solutions. Notable projects: Rooftop photovoltaic integration for food facilities, waste heat recovery in industrial compressors, and GPT applications in public building management. Dr. Gordić collaborates with municipalities and industries to develop practical solutions for energy efficiency, including thermal insulation strategies and carbon footprint reduction in urban settings. His publications frequently explore Balkan case studies, emphasizing regional sustainability challenges.

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Sam Roozbehaniمشاهده پروفایل

پژوهشگر ارشد

Technical University of DenmarkDenmark

Sam Roozbehani serves as a Postdoctoral Research Fellow at the Department of Engineering Technology and Didactics Energy Technology and Computer Science, Technical University of Denmark (DTU), Ballerup campus. His research in power systems engineering directly supports UN Sustainable Development Goals for affordable and clean energy, with expertise spanning microgrid stability, inverter control, and advanced power system protection mechanisms. His primary research domains include Microgrid Engineering, Inverter Engineering, and Reactive Power Engineering, with specialized focus on fault ride-through coordination, grid-forming/grid-following inverter architectures, and advanced control techniques like fractional-order sliding mode control. Current investigations address critical challenges in renewable integration resilience, particularly voltage stability during grid faults and optimal control of hybrid photovoltaic-battery systems in microgrids. Analysis of his 2025 publications reveals concentrated efforts on real-time solutions for inverter-based microgrid stability, with significant contributions to fault management protocols and frequency regulation in industrial energy clusters. His work demonstrates consistent emphasis on practical implementations of control algorithms for wind turbine systems and eco-industrial applications. Dr. Roozbehani actively contributes to two major research initiatives: Electric weed control in seed crops - Developing electrical methods for sustainable agricultural weed management GRACE project - Creating grid capacity-aware investment frameworks for eco-industrial clusters to optimize sector coupling and renewable integration These projects involve cross-disciplinary collaboration with DTU researchers in energy systems and environmental engineering, targeting near-term industrial implementation.

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Lorand Szaboمشاهده پروفایل

استاد

Technical University of Cluj-NapocaRomania

Lorand Szabo is a Full Professor at the Department of Electrical Machines and Drives , Faculty of Electrical Engineering , Technical University of Cluj-Napoca , Romania. He has been affiliated with this institution since 1990, transitioning from Research and Design Engineer to Lecturer (1999), Associate Professor (2007), and Full Professor (current). He also served as an Invited Professor at Pannon University (Hungary, 2007-2008) and University of Pavia (Italy, 2015). Teaching : Special Electrical Machines (1985-present), Electrical Machines and Drives (1996-present), Computer Aided Design of Electromechanical Systems (2009-present). Supervision : Ph.D. supervisor since 2007 for 8 students (6 completed). Research Focus : Linear and variable reluctance electrical machines, fault-tolerant designs, bearing fault detection in motors, and condition monitoring. His work extends to automotive applications (electric vehicles, hybrid systems), wind energy generators, and sustainable material sourcing for electrical machines. Recent Publications (2023-2025) address critical topics in sustainable mobility, including rare earth material dependency, deep-sea mining for electric technologies, battery management systems, and resource-efficient motor designs. These works reflect his interdisciplinary approach combining electrical machine innovation with environmental and industrial systems thinking. Technical Expertise : Finite element analysis (JMAG, ANSYS Motor-CAD), LabVIEW modeling, fault detection algorithms (wavelet transforms, kurtosis deconvolution), and modular motor construction for automotive and renewable energy applications.

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