جست‌وجوی استاد و پژوهشگر

Paul Savaمشاهده پروفایل

استاد

• Seismic Imaging
• Planetary Geophysics
• Wavefield Tomography
• +۵ مورد دیگر

Paul Sava is a Professor and C.H. Green Chair of Exploration Geophysics at the Colorado School of Mines, serving as Department Head of Geophysics since 2019. He holds a PhD in Geophysics from Stanford University (2005), an MSc from Stanford (1998), and an Engineer Geophysicist degree from the University of Bucharest (1995). His research focuses on seismic and radar wavefield imaging, planetary geophysics, and infrastructure monitoring. Notable contributions include advancements in wave-equation migration and planetary radar tomography. Education: PhD in Geophysics, Stanford University, 2005 MSc in Geophysics, Stanford University, 1998 Engineer Geophysicist, University of Bucharest, 1995 Research interests emphasize wavefield-based methods for subsurface imaging, planetary resource exploration, and autonomous data acquisition. Recent work explores seismic imaging of asteroids and Mars, leveraging orbital radar systems. His publications span seismic inversion, microseismic monitoring, and elastic wavefield tomography. Awards include the Reginald Fessenden Award (2007), T.K. Young Leadership Award (2020), and multiple Top 30 presentations at SEG Annual Meetings. He leads the Center for Wave Phenomena and actively collaborates with NASA and industry consortia on grants totaling over $6 million. Advising and grants involve mentoring over 30 students and postdocs, with grants focused on planetary radar imaging, seismic FWI, and Mars subsurface analysis. Key projects include the Planetary Orbital Radar Processing and Simulation System (PORPASS) and autonomous seismic exploration systems. Labs/Teams: Directly leads the Center for Wave Phenomena and the Seismic Imaging Team at CWP, advancing open-source tools like Madagascar for reproducible geophysical research.

Jason Laurieمشاهده پروفایل

مدرس ارشد

• Wave Turbulence
• Quantum Turbulence
• Nonlinear Optics
• +۲ مورد دیگر

Dr. Jason Laurie is a Senior Lecturer in Applied Mathematics at Aston University's College of Engineering and Physical Sciences, School of Computer Science and Digital Technologies. He holds a PhD from the University of Warwick and completed postdoctoral research at ENS Lyon and the Weizmann Institute. Laurie's research explores wave turbulence, quantum/superfluid dynamics, and nonlinear optics, funded by grants including a Leverhulme Project Grant (2021) and a Marie Skłodowska-Curie RISE award (2019). He teaches probability, statistics, and research methods. His recent articles focus on optical turbulence attractors and computational polynomial regression, emphasizing analytical and numerical approaches. Dr. Laurie is a member of the EPSRC Peer Review College and organizes international workshops on fluid dynamics and turbulence.

Hristo Chipilskiمشاهده پروفایل

استادیار

• Data Assimilation
• Artificial Intelligence
• Numerical Weather Prediction
• +۲ مورد دیگر

Hristo Chipilski is an Assistant Professor in the Department of Scientific Computing at Florida State University. His research focuses on data assimilation, artificial intelligence, numerical weather prediction, and atmospheric dynamics, combining theoretical, computational, and applied approaches. Education: 2021-2023 ASP Postdoctoral Fellow (NCAR), 2016-2021 PhD in Meteorology (University of Oklahoma), 2012-2016 MMet in Meteorology and Climate (University of Reading, UK) Research Interests: Data assimilation (optimal combination of models and observations) drives his work, particularly for atmospheric systems. He explores AI integration with traditional assimilation methods, targeting convective-scale weather prediction and real-time high-performance computing applications. His studies analyze bore-generating convection, cloud microphysics, and multiscale dynamics. Article Trends: Recent publications emphasize nonlinear ensemble filtering techniques, diffusion models, and generative AI for data assimilation in geophysical systems. Topics span surface quasi-geostrophic dynamics, partial observation handling, and real-time numerical weather prediction (NWP) frameworks optimized for high-performance computing.

Rabia Djellouliمشاهده پروفایل

استاد

• Mathematical and Numerical Aspects of Wave Propagation
• Inverse Problems
• Computational Mechanics
• +۵ مورد دیگر

Rabia Djellouli is a Professor in the Department of Mathematics at California State University Northridge (CSUN), where she has been since 2003. Previously, she held academic positions at institutions including the University of Colorado Boulder (1996–2003) and Tunisian universities such as Ecole Supérieure des Télécommunications de Tunisie (1995–1996). She earned her Ph.D. in Mathematics from the University of Paris-XI and École Polytechnique (France) in 1988, following degrees from the University of Paris-Sud and University of Algiers. Research Interests focus on wave propagation phenomena, inverse problems, computational mechanics, and biomedical engineering. Her work spans mathematical physics, numerical analysis, and bio-mathematics, with applications in optical fibers, fluid-structure interactions, and medical imaging. Her publications emphasize solutions to acoustic and elastoacoustic scattering problems, numerical methods for partial differential equations, and applications in biomedical engineering such as fibrous capsule growth modeling. She has secured grants from NSF and industry partners like Medtronic, supporting research in computational methods and medical device innovation. Service & Mentoring includes roles as Department Graduate Committee Chair, organizer of student research symposia, and mentor for over 20 undergraduate and graduate students. She has led NSF-funded programs like PUMP (Preparing Undergraduates through Mentoring toward Ph.D.s), fostering student research in mathematics. Affiliations include the College of Science and Mathematics at CSUN, and collaborations with institutions like INRIA (France) through international research initiatives.

Hamid Sarlakمشاهده پروفایل

دانشیار

• Fluid Mechanics
• Turbulence Modeling
• Aerodynamics
• +۱ مورد دیگر

Hamid Sarlak is an Associate Professor at the Department of Wind Energy, Technical University of Denmark (DTU). His research focuses on fluid mechanics, turbulence modeling, aerodynamics, and renewable energy systems. He holds a Ph.D. from DTU (2014), an M.Sc. from Sharif University of Technology (2010), and a B.Sc. from Amirkabir University of Technology (2007). He has conducted research on wind turbine design, solar chimney systems, and offshore wind energy technologies. His work contributes to UN Sustainable Development Goals related to affordable and clean energy (SDG 7) and climate action (SDG 13). Key research areas include wake interaction dynamics, floating offshore wind turbines, and thermal energy storage systems. He has led and participated in projects such as DigiWind (2024–2027) and IEA Wind Task 19 and 54 (cold-climate wind energy). His recent articles investigate wake interactions in FOWT rotors, solar chimney performance under crosswind, and wave excitation effects on offshore platforms. His educational contributions include co-authoring sections in DTU’s International Energy Report 2024. He has collaborated extensively with institutions like Johns Hopkins University and contributed to CFD simulations of wind turbine wakes and wave-energy converters. His work emphasizes numerical modeling, experimental validation, and sustainable energy solutions.

Ahmad Barariمشاهده پروفایل

استاد

• Advanced Manufacturing Technologies
• Digital Manufacturing
• Precision Manufacturing
• +۷ مورد دیگر

Dr. Ahmad Barari is a Professor in the Department of Mechanical and Manufacturing Engineering at the University of Ontario Institute of Technology. He holds a PhD in Mechanical Engineering from Western University (2006), MSc from Sharif University of Technology (1997), and BSc from Amirkabir University of Technology (1995). His research focuses on advanced manufacturing technologies, additive manufacturing, coordinate metrology, surface integrity, and design optimization. He has authored numerous publications and serves on multiple international conference committees. Education highlights include: PhD, Mechanical Engineering, Western University, 2006 MSc, Mechanical Engineering, Sharif University of Technology, 1997 BSc, Mechanical Engineering, Amirkabir University of Technology, 1995 Research interests span Advanced Manufacturing Technologies, Digital Manufacturing, Precision Manufacturing, and FEA-Based Design Optimization. He has contributed to innovations in additive manufacturing processes, surface quality analysis, and computational metrology. His work addresses challenges like measurement uncertainty, surface tribology, and topology optimization. Notable awards include the Best Paper Award at IMS2016 and multiple recognitions as academic advisor for student projects. He actively participates in professional activities such as organizing conference sessions and serving on review panels for NSERC, CFI, and OCE. His professional roles include organizing tracks at ASME, CAD Conferences, and IMECE events, reflecting his leadership in advancing manufacturing research. He also contributes to academic governance through roles like Design Chair for capstone projects.

• Robotics
• Control Systems
• Nonlinear Control
• +۵ مورد دیگر

Dr. Maarouf Saad is a Lecturer in the Department of Electrical Engineering at École de Technologie Supérieure (ÉTS), Université du Québec. He holds a B.Sc.A. and M.Sc.A. from Polytechnique Montréal and a Ph.D. from McGill University. His research spans robotics, control systems, and sustainable energy applications, with a focus on nonlinear control, UAVs, exoskeleton rehabilitation systems, and smart grid technologies. Education: B.Sc.A., M.Sc.A. (Polytechnique Montréal), Ph.D. (McGill) Research Units: GREPCI (Power Electronics), SYNCHROMEDIA (Telepresence), INIT Robots (Haptic Interfaces) His work integrates adaptive control algorithms with artificial intelligence in robotics, particularly for rehabilitation and aerospace systems. He has pioneered fixed-time sliding mode controllers for quadrotors and developed impedance-based methods for distribution system monitoring. In smart grids, he focuses on voltage stability analysis and distributed generation optimization. Key research trends include nonlinear control of electrohydraulic systems, modeling of flexible manipulators, and cooperative control strategies for multi-agent systems. His publications emphasize practical implementations in real-world scenarios, from autonomous airships to exoskeletons for upper-limb rehabilitation. Dr. Saad supervises numerous graduate students across diverse projects, including UAV control, cable robot rehabilitation systems, and energy management in hybrid microgrids. His collaborations extend to institutions like CAE Inc. and laboratories in telepresence and robotics.

• Pure mathematics
• Mathematical physics
• Partial differential equations

Assoc Prof Yao Yao is an Associate Professor in the Department of Mathematics at the National University of Singapore (NUS) and serves as Vice Dean of the NUS Graduate School. Her research focuses on nonlinear partial differential equations (PDEs) arising in fluid mechanics and mathematical biology. She has held academic positions at NUS since 2015, previously serving as an Assistant Professor at Georgia Tech (2013–2015), and completed her postdoctoral training at the University of Wisconsin-Madison. Her work integrates analytical techniques with numerical methods to study phenomena such as fluid dynamics, chemotaxis, and aggregation-diffusion processes. Research interests include: 1) Analysis of free boundary problems in fluid dynamics (e.g., Euler equations, porous media flows), 2) Mathematical modeling of biological processes (e.g., chemotaxis-driven pattern formation, species competition), and 3) Stability and long-time behavior of PDE systems. Notable contributions include studies on singularity formation in SQG patches and aggregation-diffusion equations, as well as symmetry properties of steady states. Selected awards and recognitions include editorial roles at journals such as Nonlinearity and SIAM Journal on Mathematical Analysis . Yao's work frequently addresses interfacial dynamics and energy methods in PDE analysis.

• Economic Model Predictive Control
• Stability of Nonlinear Systems
• Chemical Reaction Networks Theory
• +۵ مورد دیگر

David Angeli is a Professor of Nonlinear Network Dynamics in the Department of Electrical and Electronic Engineering at Imperial College London's Faculty of Engineering. Affiliations: Control and Power Research Group Energy Futures Lab His research focuses on Economic Model Predictive Control, Stability of Nonlinear Systems, Chemical Reaction Networks Theory, Systems Biology, and Control of Smart Grids. He develops theoretical frameworks for networked systems with applications in energy infrastructure and biological processes, emphasizing robustness and scalability in distributed settings. Recent publications (2023-2025) highlight work on distributed control algorithms, Lyapunov-based stability certification, and small-gain theorems for interconnected systems. His research bridges control theory, game theory, and machine learning to solve problems in cyber-physical systems, particularly in resilient consensus protocols and economic optimization for heterogeneous networks. As a core member of the Control and Power Research Group and Energy Futures Lab, he contributes to sustainable energy solutions and advanced control methodologies for complex networked systems.

• Model Predictive Control (MPC)
• Optimization Techniques
• Aerospace Engineering
• +۳ مورد دیگر

Eric Kerrigan is a Professor of Control and Optimization at Imperial College London's Department of Electrical and Electronic Engineering, part of the Faculty of Engineering. He holds a joint appointment in the Department of Aeronautics. His research focuses on Model Predictive Control (MPC), numerical optimization techniques, and their applications in aerospace, renewable energy, and information systems. Key projects include developing real-time optimization algorithms for embedded systems, co-design frameworks for closed-loop systems, and drag reduction in aerodynamics. He has supervised over 30 PhD students and post-doctoral researchers, many of whom have secured academic positions. Education: PhD in Control Engineering from the University of Cambridge and BSc in Electrical Engineering from the University of Cape Town. Research interests emphasize robust control methods, dynamic optimization, and interdisciplinary applications. Notable contributions include the ICLOCS (Imperial College Optimal Control Software) toolbox and frameworks for energy-efficient UAV communication networks. His work is funded by EPSRC, the European Commission, and industry partners like Siemens and ESA. Funding and collaborations include grants from the Royal Academy of Engineering and Royal Society, with consulting roles in industrial control systems. Editorial roles include Associate Editor for IEEE Transactions on Automatic Control and former Senior Editor for IEEE Transactions on Control Systems Technology . Labs and affiliations include the Control and Power Research Group, Energy Futures Lab, and Space Lab at Imperial College.

• Geotechnical Engineering
• Computational Mechanics
• Soil Mechanics
• +۴ مورد دیگر

James Doherty is an Associate Professor in the Department of Civil, Environmental and Mining Engineering at The University of Western Australia (UWA), affiliated with the UWA Oceans Institute. His work focuses on geotechnical engineering and cloud computing technologies, emphasizing automation of data interpretation and optimization of engineering design workflows. He leads research in numerical methods, soil-structure interaction, and offshore wind infrastructure, with over 80 peer-reviewed publications. Doherty founded the open-access geocalcs.com platform, serving 1,000+ users globally with engineering design tools derived from his research. He has developed cloud-based platforms for companies like Fugro, achieving significant computational efficiency gains. His expertise aligns with UN Sustainable Development Goals related to infrastructure and sustainable energy.

Oleksiy Klymenkoمشاهده پروفایل

مدرس ارشد

• Model-Based Process Design
• Mathematical Modelling in Natural Sciences
• Uncertainty Quantification
• +۳ مورد دیگر

Dr. Oleksiy Klymenko is a Senior Lecturer in Chemical Process Engineering at the University of Surrey, affiliated with the School of Chemistry and Chemical Engineering and the Institute for Sustainability. He holds a DPhil and specializes in model-based process design, mathematical modeling, and uncertainty quantification. Research Interests: Model-based design and optimization of process systems Mathematical modeling in natural and life sciences Uncertainty quantification, particularly global sensitivity analysis Teaching: Module leader for three M-level modules: ENGM071 Process and Energy Integration (MSc) ENGM214 Process Modelling and Simulation (MSc/Year 4 MEng) ENGM256 Technology, Business and Research Seminars (MSc/Year 4 MEng) Contributes to a Year 2 BEng/MEng module. Research Trends: Publications focus on antimicrobial technologies, energy systems optimization, and electrochemical simulations. Recent work includes 3D modeling of microbial dynamics, sustainable energy design, and the development of tools like KISSA software for electrochemical analysis. Advising & Grants: No explicit student advisees or grant details provided in texts. Research collaborations likely underpin his work in interdisciplinary areas like food safety and energy systems. Labs/Teams: Part of the Institute for Sustainability at Surrey, collaborating on projects aligning with sustainable development goals, particularly in energy and food systems.

Dennice F. Gaymeمشاهده پروفایل

دانشیار

• Wall-Bounded Turbulent Flow
• Wind Farm Modeling and Control
• Grid Integration of Renewable Energy
• +۳ مورد دیگر

Roles and Affiliations: Dennice F. Gayme is an Associate Professor in the Department of Mechanical Engineering at Johns Hopkins University's Whiting School of Engineering. She holds secondary appointments in Electrical and Computer Engineering and Environmental Health Engineering. She serves as a member of the Ralph O’Connor Sustainable Energy Institute (ROSEI) leadership council and is the faculty advisor for the Society of Women Engineers (SWE) and Hopkins Students Wind Energy Team (HSWET). Education: Bachelor’s in Mechanical Engineering and Society, McMaster University (1997) MS in Mechanical Engineering, UC Berkeley (1998) PhD in Control and Dynamical Systems, Caltech (2010) Postdoctoral Fellow in Computing and Mathematical Sciences, Caltech (2010–2012) Research Interests: Her work focuses on modeling, analysis, and control of large-scale networked systems in applications such as wall-bounded turbulent flows, wind farms, and power grids. Key areas include: Control systems for renewable energy integration Wake dynamics and wind farm optimization Fluid-structure interactions and turbulence Networked dynamical systems and distributed control Her lab employs computational methods from fluid mechanics, applied mathematics, and optimization. Recent Research Trends: Articles emphasize interdisciplinary approaches combining turbulence modeling, wind energy systems, and control theory. Key themes include wake steering optimization, offshore wind farm dynamics, and turbulence control using riblet surfaces. Recent work also explores climate resilience in energy systems and market mechanisms for renewable integration. Awards and Recognition: NSF CAREER Award (2017) ONR Young Investigator Program Award (2017) JHU Discovery Awards (2019, 2022, 2024) IEEE Senior Member and SIAM/APS/ASME Fellow Advising and Grants: Advised over 10 PhD students, including Carl Shapiro, Ismail Hameduddin, and Genevieve Starke. Secured grants from NSF, ONR, and JHU. Her team developed the JHTDB-wind database for wind farm research. Labs and Collaborations: Leads the Networked and Spatially Distributed Systems Research Group. Collaborates with institutions like Portland State University on offshore wind potential. Serves on editorial boards for Physical Review Fluids and Annual Review of Fluid Mechanics .

• Computational Fluid Dynamics
• High-Performance Computing
• Turbulence Simulation
• +۳ مورد دیگر

Martin Karp is a Research Fellow and postdoctoral researcher at KTH Royal Institute of Technology's Department of Engineering Mechanics, working under Dan Henningson. His research focuses on high-fidelity numerical simulations of turbulence and transition, with a specialization in high-performance computing (HPC) and supercomputing architectures. He holds a PhD in computer science from KTH and an MSc in Engineering Physics from Lund University, complemented by studies at ETH Zürich's computer science department. His research interests explore computational limits in nonlinear chaotic systems and future computational advancements. He leads the development of the Neko framework, a scalable simulation tool for extreme-scale CFD with extensive accelerator support. Karp's work emphasizes GPU and FPGA acceleration, parallel computing, and optimizing algorithms for heterogeneous architectures. Key contributions include large-scale turbulence simulations using GPUs, reducing communication in conjugate gradient methods, and evaluating FPGA-based flow solvers. His publications span journals like Concurrency and Computation and Scientific Reports , with conference presentations at IEEE Cluster, PASC, and HPCAsia. Karp's research bridges theoretical computational limits and practical HPC implementation, addressing challenges in precision, scalability, and hardware utilization. His educational background combines engineering physics with computer science, enabling interdisciplinary approaches to fluid dynamics and high-performance simulation. Current projects aim to push the boundaries of computational fluid dynamics through novel algorithm design and leveraging emerging hardware capabilities.

Arnold Neumaierمشاهده پروفایل

استاد

• Global Optimization
• Heuristic Optimization
• Nonlinear Optimization
• +۶ مورد دیگر

Arnold Neumaier is a Full Professor (Chair for Computational Mathematics) at the Faculty of Mathematics, University of Vienna, Austria. His research focuses on global optimization, heuristic optimization, nonlinear optimization, and optimization under uncertainty. He leads a research group developing state-of-the-art software for optimization, numerical analysis, and statistics. Collaborations include work on global optimization with Immanuel Bomze and Vladimir Kolmogorov, heuristic optimization with Nysret Musliu and Günther Raidl, and optimization for data analysis with Dan Alistarh and Radu Boț. Neumaier holds a Ph.D. from the Free University of Berlin (1977) and has held academic positions at the University of Freiburg (1987–1993), AT&T Bell Laboratories (1993–1994), and visiting roles at Princeton University, the University of Nice, and RWTH Aachen. His work spans computational mathematics, quantum physics, and mathematical software development. He maintains extensive web resources on optimization and numerical analysis. Research interests include algorithmic software development, verified computing, mathematical modeling languages, uncertainty modeling, and quantum physics. His group comprises 1 full professor, 1 associate professor, 1 university assistant, 3 postdocs, and multiple PhD students. Key contributions include the 'Global Optimization' WWW site and foundational work in causal perturbation theory for quantum field theory.