جست‌وجوی استاد و پژوهشگر

Ayşe Gül Güngörمشاهده پروفایل

استاد

• Turbulent Boundary Layers
• Adverse Pressure Gradient
• Direct Numerical Simulation
• +۳ مورد دیگر

Ayşe Gül Güngör is a Professor at Istanbul Technical University's Department of Aerospace Engineering. Her research focuses on turbulent boundary layer dynamics, pressure gradient effects, and advanced simulation techniques like Large Eddy Simulation (LES) and Lattice Boltzmann methods. Institution: Istanbul Technical University Department: Aerospace Engineering Research Interests: She investigates fundamental aspects of turbulent flows, including: Pressure force interactions in boundary layers Curvature effects on bluff-body wakes High-accuracy reactive flow solvers for combustion 3D velocity field modeling Statistical and dynamic properties of turbulence Hybrid numerical methods for complex geometries Publication Trends: Recent works emphasize computational fluid dynamics (CFD) applications, turbulence modeling in combustion systems, and pressure-driven flow instabilities. Collaborations with international researchers (e.g., Y. Maciel, D. Rodríguez) highlight cross-disciplinary projects. Grants & Projects: As Principal Investigator (PI), she leads multiple funded projects including: Hybrid Lattice Boltzmann-Finite Volume Method development (TUBITAK) Hydrogen-Enriched Methane Flame analysis (BAP) Novel Reactive Flow Solvers for Turbulent Combustion (TUBITAK) Direct Numerical Simulation of boundary layer properties (BAP)

Mohammad Omidyeganehمشاهده پروفایل

مدرس ارشد

• Computational Fluid Dynamics
• Large-eddy Simulations
• Direct Numerical Simulations
• +۱۱ مورد دیگر

Dr. Mohammad Omidyeganeh is a Senior Lecturer and Deputy Head of Engineering at City, University of London, where he has been employed since 2013. He previously served as a Lecturer (2013-2022) and has held various administrative roles including Programme Director for Mechanical Engineering and Aeronautics (2019-2021) and Admission Tutor (2014-present). His academic career began with a Post-doctoral Fellowship at Queen's University in Canada following completion of his PhD. Dr. Omidyeganeh's educational background includes: PhD in Mechanical Engineering, Queen's University, Canada (2013) MSc in Chemical Engineering (Environmental Engineering), University of Calgary, Canada (2008) BSc in Electrical Engineering, Sharif University of Technology, Iran (2005) Joint BSc in Petroleum Engineering, Sharif University of Technology and Petroleum University of Technology, Iran (2005) His primary research interests focus on computational fluid dynamics, particularly large-eddy and direct numerical simulations. He specializes in immersed-boundary methods and fluid-structure interaction, with applications in environmental fluid dynamics, geophysical flows, and aerofoil design. His work spans from river flows and sediment transport to quiet aerofoil development and brain modeling, demonstrating a broad interdisciplinary approach to fluid dynamics problems. Analysis of Dr. Omidyeganeh's recent publications reveals a strong focus on canopy flows, aeroacoustic optimization, and fluid-structure interactions. His work frequently employs computational methods to study turbulent flows over various geometries, with particular attention to drag reduction and flow control mechanisms. The research shows increasing collaboration with international teams and application to both environmental and engineering challenges. Dr. Omidyeganeh has supervised multiple PhD students including Alessandro Monti (primary supervisor), Carlo Suardi, Marco Rosti, and others working on topics related to turbulent flows, aerofoil design, and computational fluid dynamics. His research has been supported by projects including the PELSKIN project, which investigated surface coatings in aeronautics. He leads the Computing 2 Course in module ME2111 and has been instrumental in developing computational approaches to fluid dynamics problems, particularly those involving complex geometries and fluid-structure interactions. His laboratory work focuses on numerical simulations of environmental flows and aerofoil design optimization.

Narakorn Srinilمشاهده پروفایل

دانشیار

• Fluid-Structure Interaction
• Flow-Induced Vibrations
• Offshore Engineering
• +۳ مورد دیگر

Dr. Narakorn Srinil is an Associate Professor in Subsea Engineering at the School of Engineering, Newcastle University. He leads the FlexNARA research team focusing on Fluid-Flexible Structure Interactions for offshore infrastructure. His work bridges offshore oil & gas and renewable energy sectors, emphasizing predictive modeling of ocean current, wave, and ice loads. Reader/Associate Professor in Subsea Engineering, Newcastle University (since 2022) PhD Supervision in projects like 'Renewable Energy from Natural Flow Phenomena' (2021-2025) EPSRC Grant Holder for CableDyn (2022-2025) and MUFFINS (2018-2022) Royal Society & NSFC Awardee for High-Fidelity Modeling of Flow-Induced Vibrations (2019-2022) Research spans flow-induced vibrations (VIV, MFIV, IIV, WCIV) in offshore/maritime engineering, energy transition systems, and carbon capture pipelines. Key methodologies include phenomenological models, CFD simulations, and experimental validations in circulating water flumes. Recent publications analyze vortex-induced vibrations in S-shaped risers, turbulence characteristics in pulsatile flows, and AI-driven multiphase flow predictions. Awards include British Council Eco-NICE (2024-2026), EPSRC CableDyn (2022-2025), and Royal Society collaborations. Teaching involves advanced modules: MAR8052 - Dynamics of Subsea Installations , MAR8069 - Renewable Marine Structures , and MAR8011 - Offshore Installation Dynamics . Supervised over 50 MSc theses on topics like slug flow FIV, pipeline fatigue analysis, and hybrid riser systems.

• Astrophysics
• Stellar Evolution
• Nucleosynthesis
• +۶ مورد دیگر

Professor Raphael Hirschi (Lennard-Jones School of Chemical and Physical Sciences, Keele University) is a leading astrophysicist specializing in stellar evolution, nucleosynthesis, and 3D hydrodynamic simulations. With a PhD from Geneva Observatory and postdoctoral experience at the University of Basel, he joined Keele in 2007 as an RCUK fellow, becoming Professor in 2018. His work bridges observational astrophysics, nuclear physics, and computational modeling. Developed 3D hydrodynamic constraints for 1D stellar models Co-discoverer of 320 solar-mass stars (Crowther et al. 2010) Chair of the ChETEC COST Action (chemical evolution collaborations) Research Interests include: Stellar nucleosynthesis (s-process, p-process, weak s-process) Massive star evolution (rotation, metallicity, supernovae) 3D hydrodynamic simulations of convective shells and turbulence Population III stars and early universe chemical enrichment Recent trends in his publications focus on multi-dimensional stellar modeling , with collaborations across computer science and nuclear experiments (e.g., LUNA facility). Key projects include SHYNE (ERC-funded) and NuGrid simulations. Scientific Awards include the Plantamour-Prevost Prize for early-career research excellence. Teaching modules: Nuclear and Particle Physics (PHY-20009) Applied Physics and Emerging Technologies (PHY-20033) Physics of Fluids (PHY-30030) Particle Physics and Accelerators (PHY-30033)

• Fluid Dynamics
• Turbulence
• Aerospace Engineering
• +۴ مورد دیگر

Michele Iovieno is an Associate Professor in the Department of Mechanical and Aerospace Engineering (DIMEAS) at the Polytechnic University of Turin. He is a member of the College of Mechanical, Aerospace and Automotive Engineering and teaches courses in Aerospace Engineering at both undergraduate and graduate levels. His academic career spans multiple doctoral cycles (28th through 40th) in Aerospace Engineering and Fluid Dynamics programs. Dr. Iovieno's research focuses on fluid dynamics, particularly turbulence and particle-laden flows. His work explores fundamental aspects of turbulent heat transfer, direct numerical simulation (DNS) of turbulent flows, and Large Eddy Simulation (LES) techniques. His research lines include particle-laden streams, mixed convection phenomena, and non-isothermal turbulent flows with suspended particles. His work aligns with broader societal goals including climate action, quality education, and industry innovation. Analysis of his recent publications (2023-2025) reveals a strong focus on heat transfer mechanisms in particle-laden turbulent flows, with particular attention to thermal feedback effects, particle clustering phenomena, and mixed convection regimes. His research demonstrates sophisticated numerical approaches to studying complex multiphase flow phenomena, often employing direct numerical simulation techniques to examine fundamental fluid-particle interactions at high resolution. Dr. Iovieno actively supervises PhD students in the Aerospace Engineering program, with current advisees working on topics including particle-laden channel flows, heat transfer in non-isothermal turbulent flows, and mixed convection phenomena. His teaching portfolio includes courses on Fluid Dynamics for the Environment and Energy, Aerodynamics, and Thermofluid Dynamics across multiple academic years. He is affiliated with research groups focused on Fluid Dynamics and Boundary Layer Flow within DIMEAS, contributing to the department's expertise in computational fluid dynamics and turbulence research. His work connects theoretical fluid mechanics with practical applications relevant to aerospace engineering and environmental fluid dynamics.

Olga Shishkinaمشاهده پروفایل

پژوهشگر

• Turbulent Convection
• Fluid Dynamics
• Heat Transfer
• +۳ مورد دیگر

PD Dr. Olga Shishkina is a Max Planck Research Group Leader at the Laboratory for Fluid Physics, Pattern Formation and Biocomplexity (LFPB) within the Max Planck Institute for Dynamics and Self-Organization in Göttingen, Germany. Her research focuses on turbulent thermal convection, numerical simulations, and heat/momentum transport in complex fluid systems. Fields of Interest : Turbulent Convection, Fluid Dynamics, Heat Transfer, Numerical Simulations, Thermal Boundary Layers, Scientific Computing Dr. Shishkina's work explores turbulent Rayleigh-Bénard convection, magnetoconvection, and rotating/centrifugal convection through direct numerical simulations (DNS). Key themes include scaling relations, boundary layer dynamics, and the impact of geometric constraints, magnetic fields, and buoyancy forces on flow structures. Her recent publications (2024–2025) analyze scaling laws in sheared/rotating convection, heat transport in annular/cylindrical geometries, and machine learning applications for cosmological simulations. The group also investigates liquid metal convection, subcritical chaos, and superstructures in confined turbulent flows. Contact : +49 551 5176-335 | +49 551 5176-302 | olga.shishkina@ds.mpg.de Address : Room 2.124, Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, 37077 Göttingen, Germany

Gautam Biswasمشاهده پروفایل

استاد

• Fluid Mechanics
• Thermal Sciences
• Computational Fluid Dynamics
• +۴ مورد دیگر

Gautam Biswas is a J C Bose National Fellow and Professor in the Department of Mechanical Engineering at the Indian Institute of Technology Kanpur . A distinguished academician and researcher, he specializes in Fluid and Thermal Sciences , with a prolific publication record and numerous prestigious fellowships to his credit. Education: PhD, IIT Kharagpur (1985) MTech, IIT Kharagpur (1981) BE, IIEST, Shibpur (1979) Research Focus: His work spans Computational Fluid Mechanics , Heat Transfer , Free Surface Flows , Turbulence , and Microfluidics . His studies delve into complex phenomena such as drop coalescence, microdrop impact, electrohydrodynamic effects on boiling, and droplet dynamics in confined geometries. Scientific Recognition: He is a Fellow of the Indian National Science Academy (INSA) , Indian Academy of Sciences , National Academy of Sciences, India , Indian National Academy of Engineering , and the American Society of Mechanical Engineers (ASME) . He has been honored with the J C Bose National Fellowship by the Department of Science and Technology, Government of India. Contact & Location: Office: NL 302, Northern Laboratories, IIT Kanpur Email: gtm@iitk.ac.in Phone: +91-512-259-7656

Nils Christiansenمشاهده پروفایل

پژوهشگر

• Offshore Renewable Energy
• Marine Ecosystem Dynamics
• Ocean Hydrodynamics
• +۴ مورد دیگر

Dr. Nils Christiansen is a Researcher at the Institute for Coastal Systems - Analysis and Modelling (Helmholtz-Zentrum Hereon) and affiliated with the Institute of Oceanography at Universität Hamburg . His work focuses on quantifying the environmental impacts of offshore renewable energy infrastructure, particularly offshore wind farms and hydrogen production facilities, on ocean dynamics and marine ecosystems. Key Research Areas: Offshore Wind Energy, Ocean Stratification, Hydrodynamics, Marine Ecosystem Modeling, Climate Interactions, Sediment Biogeochemistry Projects: CoastalFutures (BMBF), CLICCS, WIPAFF, EXC 2037 'Climate, Climatic Change, and Society' (DFG) Christiansen employs numerical modeling (e.g., ECOSMO, COSMO-CLM) to study large-scale alterations in primary production, bottom shear stress, and dissolved oxygen levels in the North Sea. His 2022 research highlighted ±10% local changes in annual primary production and 10% sediment carbon increases in southern North Sea deeper waters due to wind farm-induced circulation changes. Findings indicate that offshore renewable energy developments can restructure coastal ecosystems at basin scales through wake-driven upwelling/downwelling dipoles and reduced residual currents. These effects may influence trophic interactions (e.g., 12% zooplankton biomass increase in stratified zones) and require adaptive marine management strategies for fisheries and protected areas. Modeling Expertise: 3D Coupled Physical-Biogeochemical Systems, Wind Wake Parameterization, Tidal-Stratification Coupling Policy Relevance: Informing the Esbjerg Declaration (150 GW North Sea wind by 2050), marine spatial planning, and hypoxia mitigation

• Energy and combustion science
• Propulsion and power generation
• Experimental combustion
• +۱۰ مورد دیگر

Professor Ramanarayanan Balachandran is Professor of Energy Technologies in the Department of Mechanical Engineering at University College London. His academic career spans over two decades with expertise in combustion science, alternative fuels, and energy technologies, focusing on experimental approaches to solve complex engineering challenges in propulsion and power generation. His educational background includes: Doctor of Philosophy from University of Cambridge (2005) Master of Science from Indian Institute of Technology, Chennai (2003) Bachelor of Engineering (Honours) from Madurai Kamaraj University (1998) Professor Balachandran's research focuses on energy and combustion science with applications to propulsion and power generation systems. His work spans experimental combustion, multiphase flow dynamics, and alternative fuel technologies. He has made significant contributions to understanding hydrogen and ammonia combustion, thermoacoustic instabilities in gas turbine combustors, and pollutant formation mechanisms. His research employs advanced laser diagnostics to study complex combustion phenomena at high temporal and spatial resolution, with strong industry collaboration particularly with Siemens Energy. His recent publication record (including works dated 2025) demonstrates a strong focus on hydrogen and ammonia combustion technologies, with particular emphasis on lean direct injection systems, combustion dynamics, and stability characteristics. The work spans fundamental research on flame structure and dynamics to applied studies addressing practical challenges in gas turbine combustors. His research team has made important contributions to understanding the transition to thermoacoustic instabilities and developing methods for their prediction and control. Professor Balachandran has received numerous prestigious awards for his research contributions: Research Excellence Award (2020) from the Combustion Institute Distinguished Paper on Turbulent Flames (2015) from the Combustion Institute Sugden Award (2011) from the Combustion Institute British Section Most Cited Author Award (2008) from Combustion and Flame Instrumentation Award (2004) from Scientific Instrument Makers Company ASEM DUO-India Professorship Fellow (2020-2022) As an educator, Professor Balachandran has taught key modules including Introduction to Thermodynamics and Fluid Mechanics, Advanced Thermodynamics and Fluid Mechanics, and Thermal Power and the Environment. His research aligns with multiple United Nations Sustainable Development Goals including Affordable and Clean Energy, Climate Action, and Sustainable Cities and Communities, reflecting the societal relevance of his work on clean energy technologies. Professor Balachandran leads an active research group at UCL equipped with state-of-the-art facilities for combustion diagnostics and alternative fuel testing, with strong international collaborations spanning the UK, Europe, and Asia.

Scott Feisterمشاهده پروفایل

استادیار

• Scientific Computing
• High-Performance Computing
• Laser-Plasma Physics
• +۴ مورد دیگر

Dr. Scott Feister is an Assistant Professor in the Department of Computer Science at California State University Channel Islands (CSUCI), where he has held a tenure-track position since 2019. His academic journey includes a B.S. in Physics from the University of Notre Dame and M.S./Ph.D. in Physics from The Ohio State University, followed by postdoctoral work at the University of Chicago and UCLA. His research focuses on scientific computing at the intersection of computer science, physics, and engineering. Primary domains include: Control systems infrastructure for high-power laser facilities Machine learning applications in experimental science High-data-rate instrumentation and embedded systems High-performance computing for plasma physics simulations Publication analysis reveals consistent focus on laser-plasma interactions (12 papers), high-performance computing (4 papers), and educational innovation (3 papers), with recent work emphasizing machine learning integration and equity-focused STEM training. He leads multiple grants involving collaborations with: Lawrence Livermore National Laboratory Lawrence Berkeley National Laboratory NVIDIA Ohio State University Argonne National Laboratory Teaching innovations include cloud-based learning environments (AWS, Replit), open-source textbooks, and hardware prototyping. He has developed 12 distinct courses and holds certifications in AWS Cloud, Mental Health First Aid, and equity pedagogy.

• Quantum Science
• Quantum Thermodynamics
• Condensed Matter Physics
• +۲ مورد دیگر

Dr. Lewis Williamson is a Research Fellow at the School of Mathematics and Physics, University of Queensland, and an affiliate of the ARC Centre of Excellence for Engineered Quantum Systems (EQUS). His academic qualifications include a Bachelor of Science (Honours), Postgraduate Diploma, and PhD from the University of Otago. His research centers on quantum science , with emphases on: Quantum thermodynamics and work extraction in coherent systems Dynamics of Bose-Einstein condensates and ferromagnetic superfluids Berezinskii-Kosterlitz-Thouless phase transitions Non-equilibrium dynamics in quantum many-body systems Recent publications (2014–2025) predominantly explore quantum phase transitions, spin vortices, and quantum heat engines, reflecting a consistent focus on statistical mechanics and quantum coherence in ultracold atomic platforms. Theoretical modeling of spinor condensates and thermodynamic processes forms the core trend across these works. He currently co-advises doctoral candidates on projects involving quantum thermal machines and many-body systems, underscoring his active supervisory role. His laboratory affiliations leverage resources from the EQUS research center for engineered quantum systems.

Nan Chenمشاهده پروفایل

دانشیار

• Applied Mathematics
• Uncertainty Quantification
• Data Science
• +۶ مورد دیگر

Nan Chen is an Associate Professor at the Department of Mathematics , University of Wisconsin-Madison , and a faculty affiliate of the Institute for Foundations of Data Science (IFDS) , a TRIPODS Phase II Initiative. His research spans applied mathematics, data science, geophysics, and machine learning, focusing on modeling complex systems, stochastic methods, numerical algorithms, and uncertainty quantification (UQ) for large-dimensional dynamics. PhD: Courant Institute of Mathematical Sciences (CIMS) & Center for Atmosphere and Ocean Science (CAOS), New York University (2016) Postdoc: CIMS, NYU (2016–2018) Advisor: Andrew Majda Master's: School of Mathematical Sciences, Fudan University (2013) Bachelor's: Mechanical Engineering, Fudan University (2010) His work emphasizes UQ, data assimilation, and predictive modeling for systems with turbulence, partial information, and non-Gaussian features. Applications include atmosphere-ocean science (e.g., El Niño, Madden-Julian Oscillation) and material science. He also develops computational tools for excitable media, neuroscience, and high-dimensional data analysis. He contributes to education through courses like Uncertainty Quantification and Data Assimilation, and public outreach via articles in Elsevier's Reference Module in Earth Systems . He co-organizes the Data Meets Dynamics workshop to promote interdisciplinary collaboration and mentorship.

• Computational Fluid Dynamics
• Multiphase Flows
• Turbulence Modeling
• +۲ مورد دیگر

Dr. Aditya Karnik is a Lecturer in Mechanical Engineering at Robert Gordon University, Aberdeen, UK, within the School of Computing, Engineering & Technology. He is affiliated with the Sustainable Energy Research Group, contributing to research in the Environment, Energy & Sustainability theme. Dr. Karnik's educational background includes a B.E., M.Tech., and Ph.D., and he holds Fellowship of the Higher Education Academy (FHEA). Prior to his current position, he worked as a Research Associate in the Department of Chemical Engineering at Imperial College London and as a Senior Development Engineer in the Multiphase Modeling Group at CD-adapco (now Siemens). Dr. Karnik's research focuses on Computational Fluid Dynamics , Multiphase Flows , and Turbulence Modeling . His recent work has particularly concentrated on gas-water multiphase flow behavior, hydrate formation in subsea pipelines, pipeline leak detection, and thermal characteristics of domestic heating systems. His research employs various computational approaches including Eulerian-Lagrangian (particle tracking) and Eulerian-Eulerian (two-fluid model) methods, with experience across the turbulence modeling spectrum from DNS to LES and RANS. Dr. Karnik has published extensively in his field, with recent publications focusing on hydrate deposition modeling, pipeline safety, and renewable energy applications. His work demonstrates a strong emphasis on practical applications of fluid dynamics in energy and environmental contexts, addressing critical challenges in subsea pipeline operations and energy efficiency. Reviewed for Applied Thermal Engineering (Elsevier) Reviewed for Industrial & Engineering Chemistry Research (ACS) Reviewed for Scientific Reports (Springer Nature) Dr. Karnik has supervised several PhD students to completion, with research topics spanning hydrate plugging risk in subsea gas pipelines, pipeline leak detection using adaptive surrogate modeling, and improvements to hydrocyclones for produced water treatment in the oil and gas industry. His teaching responsibilities include Module Co-ordination for Advanced Thermofluids and Industrial Plant courses.

• Machine Learning
• Reinforcement Learning
• Plasma Physics Simulations
• +۱ مورد دیگر

Fabian Paischer is a Researcher at the Institute for Machine Learning, Johannes Kepler University Linz (JKU), holding a Doctorate and Master of Science degree. His work bridges machine learning with high-impact scientific domains including plasma physics for fusion energy and reinforcement learning systems. Education: Doctorate (Dr.) Master of Science (MSc) His research focuses on developing neural surrogate models for plasma turbulence simulations and advancing reinforcement learning through pre-trained model modulation and human-readable memory architectures. This interdisciplinary work integrates deep learning with computational physics and autonomous decision-making, targeting applications in sustainable energy and intelligent systems where interpretability and data efficiency are critical. Analysis of his 2023-2025 publications reveals two dominant research thrusts: (1) neural operator applications for plasma edge simulations requiring long-term predictive accuracy in fusion environments, and (2) modular reinforcement learning frameworks enabling knowledge transfer between pre-trained models. These directions highlight his commitment to solving complex scientific computing challenges through novel AI methodologies. Dr. Paischer actively participates in academic communities, including the ELLIS Doctoral Symposium (2021), and maintains ongoing research output through preprints and conference publications at venues like NeurIPS and ICLR workshops.

Pietro Paolo Ciottoliمشاهده پروفایل

دانشیار

• Aerospace propulsion
• Combustion
• Turbulent flows
• +۴ مورد دیگر

Pietro Paolo Ciottoli serves as Associate Professor of Aerospace Propulsion in the Department of Mechanical and Aerospace Engineering at Sapienza University of Rome since 2024, following his tenure as Research Fellow (2013-2019) at the same institution. His academic foundation was built entirely at Sapienza University of Rome: Bachelor of Science in Aerospace Engineering (2006) Master of Science in Aeronautical Engineering (2009) PhD in Theoretical and Applied Mechanics (2013) Dr. Ciottoli's research centers on aerospace propulsion systems with specialized expertise in combustion dynamics, turbulent/multiphase flows, and gas dynamics. He integrates high-performance computing and computational fluid dynamics to advance propulsion technology, particularly in gas turbine combustors and hypersonic applications. His work bridges theoretical mechanics with practical aerospace engineering challenges. Teaching spans multiple academic levels: undergraduate courses in propulsion systems and laboratories; Master's instruction in Gas Turbine Combustors and Hypersonic Propulsion; specialized modules on turbulent combustion; and doctoral training in reacting spray modeling.