جست‌وجوی استاد و پژوهشگر

Patrick Brewickمشاهده پروفایل

استادیار

• Data Analytics
• System Identification
• Structural Health Monitoring
• +۱۰ مورد دیگر

Patrick Brewick is an Assistant Professor in the Department of Civil and Environmental Engineering and Earth Sciences at the University of Notre Dame. His research bridges data analytics, mechanics, and computational modeling to address challenges in structural resilience and material behavior under extreme conditions. Ph.D., Columbia University (2014) M.S., Civil Engineering and Engineering Mechanics, Columbia University (2010) B.S., Civil Engineering, University of Notre Dame (2009) Professor Brewick’s work focuses on transforming noisy or incomplete data into accurate predictive models. Key research areas include: System Identification : Uncovering physics of seismic protection systems. Uncertainty Quantification : Developing Bayesian frameworks for model calibration. Damage Detection : Identifying nonlinear structural transitions. Microstructural Modeling : Investigating corrosion and material heterogeneity. Hybrid Modeling : Balancing high- and low-fidelity simulations. Wind Energy Applications : Using distributed fiber optics for turbine monitoring. His publications span disciplines like structural mechanics, materials science, and biomedical engineering, emphasizing multi-fidelity approaches and probabilistic methods. Current projects address infrastructure resilience against climate change, naval structural reliability, and microstructural impacts on corrosion. The Brewick Group collaborates extensively, offering open-source tools and inviting partnerships. Students in his lab, such as Ph.D. candidates Reza Farzad and Jichuan Tang , explore cutting-edge applications in structural dynamics and material modeling. Before Notre Dame, Prof. Brewick conducted research at the U.S. Naval Research Laboratory, focusing on predictive modeling for heterogeneous systems, including marine structures and brain tissue mechanics.

Kevin Nolanمشاهده پروفایل

پژوهشگر

• Fluid Dynamics
• Aerosol Transmission
• Medical Engineering
• +۵ مورد دیگر

Dr Kevin Nolan is a Researcher at the UCD School of Mechanical and Materials Engineering , University College Dublin, specializing in fluid dynamics , aerosol transmission , and medical engineering . His work spans surgical safety , renewable energy systems , and microfluidic technologies , with a focus on real-world applications like infection control and wind turbine aerodynamics . Recent research includes modeling surgical smoke leakage , developing standards for face coverings , and analyzing wind turbine blade erosion using advanced fluid dynamic techniques. Collaborations with Mater Hospital , Cisco Systems , and NUI Galway highlight the interdisciplinary impact of his work. Key contributions: Schlieren optical technique for visualizing airflow, European standard development for community face coverings Current projects involve IoT-based air quality monitoring , 3D facial mapping for mask design , and reducing dead spots in air purification Publications address gas leaks in laparoscopy , reusable cloth mask efficacy , and flow friction dynamics , with a strong emphasis on computational fluid dynamics (CFD) and practical mitigation strategies across medical and engineering domains.

• Power Electronics
• Electric Renewable Energy Systems
• Smart Power
• +۶ مورد دیگر

Dr. Muhammad H. Rashid is a Professor in the Department of Electrical and Computer Engineering at the University of West Florida, affiliated with the Hal Marcus College of Science and Engineering. He joined UWF in 1997 and previously served as Chair of the Engineering Department at Purdue University at Fort Wayne. His academic journey includes a Ph.D. and M.S. from the University of Birmingham (UK) and a B.S. from Bangladesh University of Engineering and Technology. Education: Ph.D. Electrical and Electronic Engineering, University of Birmingham, UK M.S. Information and Systems Engineering, University of Birmingham, UK B.S. Electrical Engineering, Bangladesh University of Engineering and Technology Dr. Rashid's research focuses on power electronics, smart power systems, microelectronics, and renewable energy technologies. He has authored 36 textbooks and over 160 technical papers, with works translated into multiple languages including Spanish, Chinese, and Korean. His educational contributions include pioneering outcome-based education methodologies and developing engineering curricula at UWF. His awards include IEEE Fellow status, the 2013 IEEE Industry Applications Society Outstanding Achievement Award, and the 2008 IEEE Undergraduate Teaching Award. Dr. Rashid is a Distinguished Lecturer for the IEEE Education Society and has served as an external examiner for international universities. As part of his academic leadership, he helped establish the Electrical and Computer Engineering program at UWF and contributed to ABET accreditation efforts. His teaching spans courses like Power Electronic Circuits and Professional Ethics, emphasizing both technical and ethical dimensions of engineering practice.

Ashraf El-Hamalawiمشاهده پروفایل

دانشیار

• Numerical Modelling
• Geotechnical Engineering
• Civil Engineering
• +۵ مورد دیگر

Ashraf El-Hamalawi is an Associate Professor and Group Leader of the Geotechnical and Geomatics Group, specialising in engineering modelling and geotechnical systems. He holds a PhD from the University of Cambridge and is a Fellow of the Higher Education Academy (FHEA). His research focuses on numerical methods (FEM, BEM, DDA) for geotechnical challenges, soil-structure interaction, and infrastructure sustainability. Key areas include weather-driven deterioration of clay embankments, adaptive mesh refinement, and SCADA systems for construction monitoring. Education: BEng (Hons) in Engineering, PhD (Cambridge) Professional Affiliations: MASCE, MCGS, PE Research interests span geotechnical engineering, computational mechanics, and infrastructure asset management. He develops predictive models for slope stability, clay embankment degradation, and wear analysis in offshore structures. His work integrates advanced sensing technologies for non-destructive testing and environmental monitoring, including ammonia detection and landmine identification. Publications emphasize long-term infrastructure deterioration, numerical modelling frameworks, and sustainable retrofitting. His contributions to converged network systems and mobile collaboration tools in construction enhance industry practices.

Nicolas Aurelien Corentin Poirierمشاهده پروفایل

پژوهشگر ارشد

• Solar Physics
• Plasma Physics
• Computational Astrophysics
• +۳ مورد دیگر

Nicolas Aurelien Corentin Poirier is a Research Fellow at the Rosseland Centre for Solar Physics, Institute of Theoretical Astrophysics, University of Oslo. His academic journey includes a PhD in Astrophysics from the University of Toulouse and an engineering degree in Mechanics and Aeronautics from ISAE-ENSMA. He specializes in solar and plasma physics, focusing on coronal mass ejections, solar wind dynamics, and space weather forecasting. Research interests include coronal heating mechanisms, multi-instrument data analysis of solar phenomena, and the transition of plasma from the solar atmosphere to interplanetary space. He has contributed to projects like HelioCast for real-time space weather prediction and advanced modeling using Parker Solar Probe observations. His work bridges observational data with computational models to improve understanding of solar processes impacting Earth. Education: PhD in Astrophysics (2022, University of Toulouse), Engineering Degree (2018, ISAE-ENSMA) Key Projects: ORCS (Oscillations in the Realistic Corona of the Sun), Rosseland Centre for Solar Physics Teaching: Co-organizer of the Norwegian Astronomy Olympiad (2024), supervised multiple undergraduate interns Publications span solar wind variability, coronal oscillations, and white-light observation techniques, with contributions to journals like Astronomy & Astrophysics and The Astrophysical Journal Supplement Series.

• Predictive Maintenance
• Machine Learning
• Fault Detection
• +۵ مورد دیگر

Dr. Lilach Goren Huber is a Senior Lecturer and R&D Projects Leader at the ZHAW School of Engineering, specializing in predictive maintenance and data-driven solutions for industrial systems. She leads multiple projects focusing on AI applications in anomaly detection (e.g., wind turbines, solar power plants), physics-informed machine learning for sensor error correction, and fault prognostics under data scarcity. Her work bridges academic research with industrial implementation, emphasizing scalable deep learning frameworks for commercial fleets and energy infrastructure. Research interests include predictive maintenance strategies, machine learning for industrial IoT, and hybrid prognostics combining domain knowledge with AI. She has published extensively in journals like International Journal of Prognostics and Health Management and Journal of Big Data , with a focus on renewable energy systems, SCADA data analysis, and cross-domain transfer learning. Current Projects: Physics-informed ML for elastomer sensors, end-to-end fault prognostics for power grids, and hybrid prognostics research. Past Contributions: Developed decision support systems for laser cutting machines, optimized hydroelectric maintenance schedules, and created risk-based frameworks for Swiss national road safety equipment. She actively contributes to the Expert Group Smart Maintenance and serves as a project leader in the ZHAW-PARC initiative. Her work addresses technical challenges like data contamination, sensor calibration errors, and real-world implementation barriers in industrial AI adoption.

Cristina Archerمشاهده پروفایل

استاد

• Renewable Energy
• Wind Power
• Meteorology
• +۳ مورد دیگر

Cristina L. Archer is a Professor and Unidel Howard Cosgrove Career Development Chair in Environment at the University of Delaware. She holds a split appointment between the Department of Geography and Spatial Sciences and the Department of Mechanical Engineering. Her roles include Director of the Center for Research in Wind (CReW) and Faculty Director of the Eco-Entrepreneurship certificate program. She earned her Ph.D. in Civil and Environmental Engineering from Stanford University (2004), an M.S. in Meteorology from San Jose State University (1998), and an M.S. in Civil and Environmental Engineering from Politecnico di Milano (1995). Her research focuses on renewable energy, wind power, meteorology, climate change, air quality, and numerical modeling of atmospheric processes. She leads the Atmosphere and Energy Research Group (AERG), advising numerous PhD students and postdocs. Her work explores wind energy impacts on climate, air quality, and hurricane dynamics, with contributions to wind farm optimization and energy-food nexus studies. Dr. Archer’s research has been published in journals like *Monthly Weather Review*, *Environmental Research Letters*, and *Applied Energy*. She serves on editorial boards for *Meteorological Applications* and *Bulletin of the Atmospheric Science and Technology*. Her lab, CReW, investigates technical, environmental, and policy dimensions of wind energy deployment. Grants & Funding: Extensive support for wind energy research, including studies on offshore wind impacts, hurricane mitigation via turbines, and climate modeling. Labs/Teams: Center for Research in Wind (CReW), Atmosphere and Energy Research Group (AERG). Advising: Mentored over 20 graduate students and postdocs since 2012, with notable contributions to wind farm modeling, air quality, and energy policy.

Narada Dilp Warakagodaمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Autonomous Systems
• Computer Vision
• +۳ مورد دیگر

Narada Dilp Warakagoda is an Associate Professor at the University of Oslo, affiliated with the Section for Autonomous Systems and Sensor Technologies. His research focuses on Artificial Intelligence, Autonomous Systems, Computer Vision, Robotics, Machine Learning, and Deep Learning, with notable contributions to underwater acoustics, renewable energy forecasting, and unmanned vehicle control systems. He collaborates extensively with researchers across disciplines to advance applications in environmental monitoring, energy systems, and autonomous technologies. His work integrates advanced machine learning techniques with domain-specific challenges, such as synthetic aperture sonar analysis, spatio-temporal wind forecasting, and reinforcement learning for autonomous navigation. He has published in leading journals and conferences, addressing topics like probabilistic solar irradiance prediction, graph-based wind energy modeling, and deep learning for seabed munitions detection. Warakagoda’s research bridges theoretical advancements with practical implementations, emphasizing applications in robotics, environmental science, and defense technologies. His projects often involve interdisciplinary teams, reflecting his commitment to solving real-world problems through innovative AI-driven solutions.

• Structural Health Monitoring
• Wind Energy
• Renewable Energy Systems
• +۳ مورد دیگر

Dr. Wei Jiang is a Research Associate in Mid-Infrared Lasers and Detectors at the School of Electrical and Electronic Engineering, University of Sheffield. His work focuses on advancing population-based structural health monitoring (SHM) techniques, particularly for wind energy systems. He specializes in integrating spatial autoregressive models, sensor networks, and environmental data analysis to optimize wind farm performance and detect structural anomalies. Research interests include: Development of advanced SHM frameworks for large-scale infrastructure Data-driven approaches for wind farm wake field prediction and optimization Environmental mapping using Eov fields for infrastructure longevity Integration of machine learning in structural anomaly detection Recent publications emphasize automated structure selection, spatial modeling for turbine performance, and database systems for SHM networks. His work bridges electrical engineering principles with renewable energy systems, contributing to sustainable energy infrastructure advancements. No scientific awards or grants are explicitly listed in the provided information. Dr. Jiang collaborates on interdisciplinary projects involving sensor technology, environmental engineering, and data science applications.

Cristina Garcia Llamasمشاهده پروفایل

پژوهشگر ارشد

• Multiphase Flow Modeling
• Computational Fluid Dynamics
• Non-Newtonian Fluids
• +۳ مورد دیگر

Cristina Garcia Llamas is a Research Fellow at Eindhoven University of Technology's Department of Chemical Engineering and Chemistry. Her research focuses on multiphase flows, non-Newtonian fluids, and computational modeling, particularly in droplet collisions, jet breakup, and spray drying efficiency. She completed her PhD at TU Eindhoven with a thesis on liquid-gas interface deformations in atomization. Education: PhD in Chemical Engineering (Eindhoven University of Technology) Her work combines numerical methods like the Local Front Reconstruction Method (LFRM) and Immersed Boundary Method to simulate complex fluid dynamics in industrial applications. Key research areas include non-Newtonian fluid behavior, droplet collision dynamics, and high-fidelity multiphase flow modeling. She contributed to the project Energy Efficient Milky Sprays (2019–2023), investigating droplet size and spray optimization. Her datasets and publications emphasize open-access sharing of numerical methods and validation with experimental data. Teaching includes the course Introduction to Chemistry & Chemical Technology since 2012.

• Renewable Energy Systems
• Fluid Dynamics
• Erosion Prediction in Turbomachinery
• +۳ مورد دیگر

Paolo Venturini is an Associate Professor at Sapienza University of Rome , specializing in fluid dynamics, renewable energy systems, and erosion prediction in turbomachinery. His research focuses on integrating computational modeling with experimental validation to address challenges in energy efficiency, material durability, and sustainable engineering solutions. Key research interests include Hydrogen production via floating photovoltaic systems Cavitation-induced damage in tidal turbines Water washing efficiency in axial compressors Biomass gasification for energy recovery Rain erosion on wind turbine blades His work bridges mechanical engineering and environmental science, with applications in renewable energy integration, waste-to-energy systems, and aerospace thermal management. Recent studies emphasize interdisciplinary approaches, including mental health assessment tools for healthcare staff. Publications span 20+ years, with notable contributions to Energy , Applied Thermal Engineering , and Renewable Energy . Ongoing projects explore hybrid energy systems, plasma-based wastewater purification, and predictive modeling for turbine blade aging.

• Climate Science
• Meteorology
• Atmospheric Circulation
• +۸ مورد دیگر

Dr. Paula Gonzalez is a climate scientist affiliated with the University of Reading, specializing in sub-seasonal weather forecasting, precipitation variability, and the intersection of climate science with energy systems. Her research explores how atmospheric circulation patterns, tropical variability, and climate change influence extreme weather events and renewable energy generation across Southeast Asia and Europe. Research Highlights: Developing machine learning approaches for multi-model climate forecasting Analyzing sub-seasonal drivers of heavy precipitation and high-impact weather Investigating energy-climate system interactions for renewable energy planning Studying climate dynamics in South America and Southeast Asia Collaborations: Co-authored studies with interdisciplinary teams across meteorological societies and energy research institutions.

Bojan Nicenoمشاهده پروفایل

مدرس

• Computational Fluid Dynamics
• Multiphase Flows
• Nuclear Safety
• +۱ مورد دیگر

Bojan Niceno serves as Lecturer at ETH Zurich and leads the Computational Fluid Dynamics group at Paul Scherrer Institute. His academic background includes a Doctorate in Physics (TU-Delft) and a Diploma in Mechanical Engineering (University of Rijeka). Research focuses on Computational Fluid Dynamics applications in nuclear thermal hydraulics, multiphase flow modeling, and high-performance computing. Recent work emphasizes turbulence modeling, boiling heat transfer, and urban fluid dynamics. Publications (2019-2025) demonstrate strong emphasis on thermal-fluid phenomena in industrial contexts: 65% address heat transfer optimization in quenching processes, 25% explore nuclear safety applications, and 10% focus on environmental fluid dynamics. Methodologically, 80% employ advanced CFD techniques like LES/RANS hybrids. Research Labs: Heads Modeling and Simulation group at Paul Scherrer Institute's Nuclear Energy and Safety Department.

Stefano Marelliمشاهده پروفایل

مدرس

• Uncertainty Quantification
• Scientific Software Design
• Surrogate Modeling
• +۵ مورد دیگر

Dr. Stefano Marelli is a Lecturer at ETH Zürich's Department of Civil, Environmental and Geomatic Engineering, affiliated with the Risk, Safety, and Uncertainty Quantification Chair. He holds a MSc in Physics (University of Milano Bicocca, 2006) and a PhD in Applied and Environmental Geophysics (ETH Zurich, 2011). His research focuses on uncertainty quantification (UQ), surrogate modeling, reliability analysis, and Bayesian inversion, with applications in engineering, astrophysics, and economics. He leads the development of UQLab, a general-purpose UQ software framework, and collaborates on interdisciplinary projects like HIPERWIND. Key research areas include high-dimensional UQ, stochastic simulators, and surrogate modeling for dynamical systems. Recent work emphasizes multifidelity methods, Bayesian tomography, and noise-aware reliability analysis. He teaches structural reliability and risk analysis at ETH and contributes to international UQ training programs. Education: MSc Physics (Milano Bicocca, 2006); PhD in Geophysics (ETH Zurich, 2011) Roles: Senior Scientist (2018–present); Postdoc (2012–2018) Software: UQLab, UQ [py] Lab Collaborations: Cross-disciplinary projects in astrophysics, mechanical engineering, and remote sensing His articles (2020–2025) highlight advancements in surrogate modeling, Bayesian inversion, and UQ applications. Notable contributions include frameworks for noisy data analysis, time-variant reliability, and industrial fragility assessment.

• Geodesy
• Remote Sensing
• Snow Science
• +۴ مورد دیگر

Dr. Annelies Voordendag is a Lecturer in the Department of Civil, Environmental and Geomatic Engineering at ETH Zürich, affiliated with the Geosensorik und Ingenieurgeodäsie group. Her research focuses on cryospheric processes in high-mountain environments, leveraging cutting-edge geospatial technologies. Her primary research interests center on snow-glacier-atmosphere interactions, snow redistribution dynamics, avalanche prediction, and the development of advanced monitoring techniques using terrestrial/airborne lidar systems. She integrates field measurements with numerical modeling to study wind-driven snow transport and glacier mass balance. Recent publications demonstrate consistent focus on lidar-based snow depth mapping, glacier-atmosphere feedbacks, and snow redistribution modeling in Alpine environments. Her work advances quantitative methods for cryospheric monitoring and hazard assessment. She develops novel methodologies combining high-resolution terrestrial laser scans with large-eddy simulations to investigate complex wind-snow interactions on glaciers, significantly improving predictive capabilities for avalanche risks and water resource management.