جست‌وجوی استاد و پژوهشگر

• Renewable Energy
• Ocean Engineering
• Robotics
• +۳ مورد دیگر

Eirini Katsidoniotaki is a Postdoctoral Associate (Research Fellow) in the Department of Mechanical Engineering at the Massachusetts Institute of Technology, School of Engineering. Her research addresses critical challenges in offshore renewable energy and aquaculture technology through advanced computational and robotic systems. Her primary research areas include wave energy conversion, structural health monitoring of marine structures, and aquaculture robotics. She specializes in developing real-time monitoring solutions using digital twins, multi-fidelity modeling, and machine learning techniques. Her work integrates computational fluid dynamics with experimental validation to analyze extreme loads and improve system resilience in ocean environments. Recent projects focus on adaptive path planning for net pen inspection and surrogate modeling for wave energy farms. Analysis of her publication record reveals a strong emphasis on practical applications of computational methods to enhance safety and efficiency of offshore energy systems. Her interdisciplinary approach bridges ocean engineering, robotics, and data science to tackle complex problems in marine renewable energy, with consistent focus on real-time monitoring, structural dynamics, and extreme condition resilience.

Khristopher Kabbabeمشاهده پروفایل

مدرس

• Unmanned Aircraft Systems
• Environmental Monitoring
• Aerospace Engineering
• +۳ مورد دیگر

Khristopher Kabbabe is a Lecturer in Mechanical and Aerospace Engineering at The University of Manchester. His research focuses on developing payloads and operations for Unmanned Aircraft Systems (UAVs), including applications in environmental monitoring, emissions measurement, and volcanic plume analysis. He holds a BEng (Hons) in Aerospace Engineering (2010) and an MSc from the University of Manchester (2011). His professional experience includes roles in the UK GAMMA Programme, where he collaborated with SMEs on robotics and autonomous systems, and projects with multinational companies to advance remote sensing using UAVs. Key research areas include: UAV-based methane and CO₂ emissions monitoring Design of volcanic ash capture mechanisms Safety cases for fluidic/conventional aircraft (MAGMA project) Integration of consumer-grade hardware for onboard imaging systems He has contributed to 19 peer-reviewed publications (2014–2025), with recent work focusing on UAV applications in offshore wind farm inspection, HVDC environment safety, and volcanic plume quantification. His teaching includes advanced aerospace design projects emphasizing industrial relevance, as well as continuing professional development (CPD) courses. Notable collaborations include field campaigns in Italy (Stromboli volcano) and projects with organizations like Chulalongkorn University (ICE Summer Schools). His work aligns with UN Sustainable Development Goals related to clean energy and climate action.

Nathan Postمشاهده پروفایل

عضو هیئت علمی

• Wind Energy Optimization
• Machine Learning Applications
• Additive Manufacturing
• +۳ مورد دیگر

Nathan Post is a Research Associate Professor at Northeastern University's Roux Institute with joint appointments in Civil and Environmental Engineering and Mechanical and Industrial Engineering. His research applies machine learning to optimize physical systems in renewable energy and manufacturing. Key research areas: Machine learning for wind farm performance optimization Additive manufacturing process characterization Reverse osmosis membrane fouling mitigation Experimental mechanics for renewable energy systems Publications demonstrate cross-disciplinary approaches combining experimental mechanics with machine learning. Recent work focuses on wind turbine wake steering, corrosion-resistant alloy discovery, and drivetrain reliability prediction. Serves as technical advisor to the ReWind Network for wind blade repurposing and develops educational tools for fluid power curriculum. Research employs field data analytics from wind farm SCADA systems and laboratory-scale material testing.

Catherine Gorleمشاهده پروفایل

دانشیار

• Computational Fluid Dynamics
• Wind Engineering
• Urban Flow Simulations
• +۲ مورد دیگر

Catherine Gorle is an Associate Professor of Civil and Environmental Engineering (with courtesy appointment in Mechanical Engineering) at Stanford University. She holds BSc and MSc degrees from Delft University of Technology and a PhD from the von Karman Institute. Her research develops predictive flow simulations for sustainable building and urban design. Research integrates computational fluid dynamics with uncertainty quantification methods to model urban wind environments, wind loads on structures, and natural ventilation patterns. Recent work focuses on multi-fidelity modeling, sensor network design, and machine learning applications for urban flow prediction. Publications demonstrate consistent innovation in wind engineering methodologies, including novel approaches for inflow generation, wind farm optimization, and urban canopy modeling. A significant research stream examines wind-wave interactions and their structural impacts. She directs research on contrail formation from aviation and develops frameworks for high-fidelity simulation of environmental flows.

Iván Herráezمشاهده پروفایل

استاد

• Renewable Energy Technology
• Wind Energy
• Computational Fluid Dynamics (CFD)
• +۴ مورد دیگر

Prof. Iván Herráez is a Professor of Renewable Energy Technology with a focus on Wind Energy at the University of Applied Sciences Emden/Leer. He is affiliated with the Department of Engineering and Natural Sciences (Technik - Naturwissenschaften) and serves as the spokesperson for the Bachelor program in Sustainable Energy Systems and the international coordinator for the Natural Sciences Engineering department. His research integrates advanced computational methods like Computational Fluid Dynamics (CFD) and machine learning to optimize renewable energy systems, particularly wind energy technologies. His work spans numerical fluid dynamics, fluid-structure interaction, and system dynamics, aiming to enhance the efficiency and reliability of wind turbines through precise simulations and data-driven models. Key areas include rotor blade aerodynamics, wake behavior analysis, and the application of machine learning in renewable energy systems. He leads collaborative projects such as the IEA Task 29 Mexnext initiative, focusing on wind turbine rotor aerodynamics and experimental validation. Prof. Herráez’s publications highlight innovations in CFD modeling, blade damage detection via infrared thermography, and optimization of offshore energy export systems. His research contributes to advancing sustainable energy technologies and addressing challenges in the energy transition.

Sanjit Debمشاهده پروفایل

دانشیار

• Soil Physics
• Hydrological Modeling
• Agricultural Water Management
• +۵ مورد دیگر

Dr. Sanjit Deb is an Associate Professor of Soil Physics in the Department of Plant and Soil Science at Texas Tech University, part of the Davis College of Agriculture. His research focuses on optimizing soil and water resource management in semi-arid agricultural systems through applied soil physics, hydrological modeling, and sustainable practices. He holds a Ph.D. in Biological and Environmental Engineering from The University of Tokyo, with prior postdoctoral experience at New Mexico State University and the University of Hawaii-Manoa. Education: Bachelor's in Agricultural Engineering, Bangladesh Agricultural University Master's in Irrigation Engineering & Management, Asian Institute of Technology (Thailand) Ph.D. in Biological & Environmental Engineering, University of Tokyo (Japan) Research emphasizes soil-water-plant interactions, vadose zone hydrology, and precision agriculture strategies for improving crop productivity while conserving resources. Key areas include biochar applications, deficit irrigation, cover crop impacts, and soil health assessment in arid regions. Collaborative efforts address challenges in cotton, corn, and pasture systems across the Southern High Plains. Teaching responsibilities include courses on soil physical properties, environmental soil science, and advanced soil physics. His work integrates field experimentation, numerical modeling (e.g., HYDRUS), and remote sensing techniques to develop scalable solutions for water-limited environments. Recent research highlights include optimizing biochar rates for crop resilience under water stress, modeling root zone dynamics in cotton-weed interactions, and evaluating cover crops' role in nitrogen cycling and soil structure improvement.

Clemens Jauchمشاهده پروفایل

استاد

• Wind Energy Technology
• Grid Integration
• Renewable Energy Systems
• +۳ مورد دیگر

Prof. Clemens Jauch is a Professor at the Department of Energy and Life Science at Flensburg University of Applied Sciences, leading the Wind Energy Technology Institute. His research focuses on grid integration of wind energy, flywheel systems for inertia control, and sustainable energy solutions. He teaches in the Wind Energy Engineering program and advises projects like the Inno!Nord-HYDRAD hydraulic flywheel storage system. His work emphasizes renewable energy systems, power system stability, and reducing CO2 emissions through innovative wind turbine designs. Key contributions include the development of hydraulic-pneumatic flywheel technologies and experimental wind farm emulators. His publications highlight advancements in grid frequency control, synthetic inertia provision, and energy transition strategies. Prof. Jauch leads initiatives such as the Wind Energy Technology Institute and collaborates on projects like the 'Demonstrator for a self-regulating hydraulic flywheel storage.' His research bridges academic innovation with practical applications in sustainable energy infrastructure.

• Decision Support Systems
• Energy Policy
• Energy Management
• +۵ مورد دیگر

Chrysostomos (Charis) Doukas is a Professor at the School of Electrical and Computer Engineering of NTUA. He holds a Mechanical Engineering degree from Aristotle University of Thessaloniki and a PhD in decision support systems for energy policy and management from NTUA. His research focuses on energy policy, multi-criteria decision analysis, and AI-driven energy management systems. He has contributed over 120 peer-reviewed publications and authored books on decision models and energy systems. Education: Bachelor’s in Mechanical Engineering, Aristotle University of Thessaloniki PhD in Decision Support Systems for Energy Policy, NTUA Research Interests: Decision Support Systems for Energy Policy Energy Management & Efficiency Multi-Criteria Analysis AI Applications in Energy Climate Policy & Sustainability His recent articles emphasize AI-driven energy forecasting, optimization models for renewable integration, and energy democracy frameworks. Over 20 awards from institutions like NTUA and Hellenic Society of Operations Research highlight his contributions. He leads initiatives like ENPOWER and ENERGATE, advancing energy equity and smart cities through data-driven approaches. Labs/Teams: Involved in interdisciplinary projects on energy systems, climate policy, and AI applications. Collaborates with European and international stakeholders on energy transition strategies.

• Renewable Energy
• Solar Energy
• Wind Energy
• +۳ مورد دیگر

Sourav Khanna is a Senior Lecturer at the School of Electrical and Mechanical Engineering, University of Portsmouth, and a member of the Centre for Environmental and Renewable Energy Solutions. His research focuses on renewable energy technologies, particularly solar energy systems, wind energy, and demand-side management. Key areas include photovoltaic systems, phase change materials (PCMs), and their integration with thermal energy storage. His work spans experimental and computational studies on solar panel performance under diverse conditions, including desert climates and phase change material applications. He has contributed to optimizing hybrid energy systems and developing frameworks for solar project feasibility. Over 40 research outputs since 2013 highlight his expertise in solar thermal engineering, material science, and energy systems analysis. Publications emphasize advancements in photovoltaic-thermal (PVT) systems, PCM-based thermal management, and interdisciplinary approaches to renewable energy challenges. Collaborations include projects on smart energy grids and energy autonomy in communities like the Isle of Wight.

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.

• Artificial Intelligence
• Machine Learning
• Renewable Energy
• +۷ مورد دیگر

Prof. Ravinesh Deo is a Professor of Mathematics at the University of Southern Queensland (USQ), leading the Advanced Data Analytics Research Laboratory with 57+ researchers. He holds a PhD in Signal Processing from the University of Adelaide and has supervised over 40 PhD/Master's students. His research focuses on AI applications in energy systems, national intelligence, healthcare, and environmental science, supported by $16.1M in grants. He is a Clarivate Highly Cited Researcher (Top 1%) and Stanford Top 2% World Scientist. Education: BSc South Pacific University MSc(Hons) Canterbury University PhD Adelaide University Research Interests: Prof. Deo pioneers AI-driven solutions in renewable energy systems, predictive modeling for UV radiation, flood forecasting, and biomedical applications. His work integrates deep learning, evolutionary computation, and big data analytics. Recent trends in his publications emphasize environmental risk assessment, energy market optimization, and healthcare diagnostics through explainable AI frameworks. Grants & Recognition: He leads projects funded by the Australian Department of Defence, Queensland Government, and EU Horizon 20. Awards include Outstanding Researcher (2022/2023), Excellence in Research (2021), and six fellowships including the Endeavour Award. His lab collaborates with 190+ global institutions across five continents. Teaching & Administration: As Postgraduate Program Director for MADS/MSCN programs, he teaches engineering mathematics and supervises research projects. He also chairs editorial boards for IEEE Access, Stochastic Environmental Research, and ASCE journals. Labs & Teams: Directs USQ's Artificial Intelligence Applications Laboratory and Advanced Data Analytics group, focusing on cross-disciplinary innovation in space technologies, climate science, and national security.

Elizabeth Masdenمشاهده پروفایل

پژوهشگر ارشد

• Renewable Energy Impacts
• Seabird Ecology
• Marine Conservation
• +۳ مورد دیگر

Elizabeth Masden is a Research Fellow at the Environmental Research Institute (ERI) of the University of the Highlands and Islands (UHI), specializing in the impacts of human activities on seabird populations and marine ecosystems. Her work focuses on renewable energy development (wind, wave, tidal), oil and gas infrastructure, and marine litter, with an emphasis on cumulative environmental effects. She holds a Ph.D. from the University of Glasgow (2010) and has published extensively on seabird ecology, spatial modeling, and conservation strategies. Education : Doctor of Philosophy (2010), University of Glasgow Master of Research (2006), University of York Bachelor of Science (2004), University of St. Andrews Research Interests : Her research integrates population dynamics and spatial ecology to address challenges posed by renewable energy projects and climate change. Key areas include seabird foraging behavior, collision risk modeling, and the conservation of vulnerable species like the Great Black-backed Gull and European Shag. She also explores innovative monitoring methods to assess ecological impacts in data-sparse regions. Recent Articles : Masden’s recent work (2023–2025) addresses cumulative impacts of offshore wind farms, niche partitioning in gull species, and environmental risks of emerging technologies like floating solar photovoltaic systems. Her findings inform policy and conservation strategies to balance renewable energy expansion with biodiversity protection. Grants & Supervision : Masden has supervised 5 research projects and contributed to grants evaluating ecological monitoring needs for infrastructure development. Her collaborations span international teams and focus on mitigating human-wildlife conflicts in marine environments. Labs/Teams : She is part of the Energy Innovation Team at ERI, collaborating on projects such as the Trollvind OWF cumulative impact assessment and the GlobalSeaweedSTAR initiative. Her work often intersects with marine spatial planning and sustainable development goals.

Xiaowei Zhaoمشاهده پروفایل

استاد

• Control Theory
• Machine Learning
• Offshore Renewable Energy
• +۳ مورد دیگر

Professor Xiaowei Zhao is a Professor of Control Engineering at the University of Warwick's School of Engineering, leading the Intelligent Control & Smart Energy (ICSE) research group. He serves as Director of the EPSRC Supergen Network Plus in AI for Renewable Energy and Co-Director of the EPSRC Supergen Offshore Renewable Energy Hub. His work focuses on control theory, machine learning, and their applications in renewable energy systems, smart grids, and autonomous systems. He has secured over £40 million in grants from EPSRC, Horizon Europe, Innovate UK, and industry, establishing four state-of-the-art labs: Offshore Renewable Energy Lab, Renewable Energy Integration Lab, Hydrogen Technology Lab, and Autonomous Systems Lab. Education: PhD in Control Theory from Imperial College London (2010), postdoctoral research at the University of Oxford (2010-2013). Research interests include offshore wind farm control, energy storage, and AI-driven energy systems. Notable recognition includes being a 2024 finalist for the UK Government’s Manchester Prize for AI in public good. Grants and Projects: Over 17 grants since 2017, including EPSRC Supergen Hubs, Horizon Europe projects, and industry collaborations. Recent grants include leadership roles in the £26M EPSRC Supergen Network Plus and a £4.86M Horizon Europe grant for economic DC microgrids. Awards: Manchester Prize finalist (2024), EPSRC funding leadership, and over 90 peer-reviewed publications. His work spans reinforcement learning, control systems, and sustainable energy integration.

Vincent Moureauمشاهده پروفایل

پژوهشگر

• Combustion Modeling
• Fluid Dynamics
• Computational Fluid Dynamics (CFD)
• +۳ مورد دیگر

Vincent Moureau is a CNRS Research Fellow (HDR) at the CORIA laboratory, specializing in advanced computational fluid dynamics and combustion modeling. His research focuses on Large-Eddy Simulation (LES) of turbulent flows, spray dynamics, and thermo-acoustic instabilities in complex geometries. He is a core developer of the YALES2 solver, a high-order unstructured code for multiphase reactive flows. Positions: Research Fellow at CORIA, HDR, and affiliated with INSA de Rouen for teaching. Key Expertise: LES in gas turbines, piston engines, and wind turbines; numerical methods for HPC systems. He has taught courses on numerical methods, aerodynamics, and CFD software training. His work earned awards including the 2018 Grand Prix ONERA and the Digital Simulation Collaboration Award. His research includes industrial collaborations with SAFRAN and INRIA. Labs/Teams: Leads the YALES2 development team and contributes to the SIAME project for exascale computing. Active in the SIAME and MATI projects for aero-thermal systems and combustion modeling.

Sanjay Sharmaمشاهده پروفایل

دانشیار

• Intelligent Autonomous Control Systems
• Marine Robotics
• Artificial Intelligence
• +۴ مورد دیگر

Dr Sanjay Sharma is an Associate Professor in Intelligent Autonomous Control Systems at the University of Plymouth . He leads the Autonomous Marine Systems Research Group , focusing on AI-driven navigation and control of marine vehicles. His work spans autonomous robotics, SLAM technology, swarm robotics , and marine energy systems . Key projects include UAE Ocean (enhancing ocean forecasting in the UAE) and sustainable fisheries management in the Indian Ocean. Education : B.Tech (Electrical Engineering) from IIT Kharagpur, M.Tech (Control Systems), and PhD (Systems & Control Engineering) from the University of Sheffield. He joined Plymouth in 2007 after roles with Indian Railways and academic collaborations. Research Interests : Application of AI in marine environments, autonomous vehicle control, underwater robotics, and sensor optimization. He emphasizes safe human-machine interaction and long-duration autonomous operations . Professional Roles : Member of the Institution of Mechanical Engineers , UK Automatic Control Council , and International Federation of Automatic Control . He coordinates training programs in oceanography and collaborates on offshore wind farm maintenance systems. Future Work : Expanding autonomous marine tech for sustainable energy, fisheries, and coastal management. He advocates for public trust in autonomous systems through transparency and rigorous testing .