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Ahmad ShakibaeiniaView profile

Professor

• Hydraulic Engineering
• Environmental Fluid Mechanics
• Multiphase Flow Modeling
• +3 more

Ahmad Shakibaeinia is a Full Professor at the Department of Civil, Geological and Mining Engineering in Polytechnique Montréal , holding the Tier 2 Canada Research Chair in Digital Hydrosystems . He serves as a researcher in the Experimental and Digital Water Flow Engineering Group (GENIE EAU) and is affiliated with the Interuniversity Study Center for Structures under Extreme Loads (CEISCE) . Research Domains : Computational fluid mechanics, multiphase flows, granular flow dynamics, cold-region hydraulics, fluvial mechanics Methodologies : Specializing in mesh-free particle methods (SPH, MPS) for simulating complex hydro-environmental flows His work focuses on multi-physics hydro-environmental flows involving water-air-sediment-ice interactions, with applications in flood risk assessment , tailings dam breach modeling , and cold-region river dynamics . Recent publications demonstrate expertise in floating breakwater systems , microbial risk assessment , and ice-structure interaction simulations . Key scientific contributions include: Developing enhanced weakly-compressible MPS/SPH methods for free-surface and granular flows Pioneering fully Lagrangian DEM-MPS models for ice-wave dynamics Creating integrated numerical frameworks for cold-region water quality assessment He has supervised 12 graduate students (3 PhD, 9 Master's) and secured multiple NSERC Alliance Grants for projects on climate change impacts and critical infrastructure vulnerability . His 74 publications span topics from sediment transport to particle method development , with significant contributions to oil sands tailings dam failure and transboundary river pollution understanding.

• Fluid Dynamics
• Computational Fluid Dynamics
• Screw Compressors
• +5 more

Aleksandar Kovacevic is a Professor at City, University of London, specializing in mechanical engineering with a focus on fluid dynamics and positive displacement machinery. With over two decades of research experience since completing his doctoral studies at City University London in 2002, he has established himself as a leading expert in screw compressor technology and computational fluid dynamics. Dr. Kovacevic's research spans multiple areas of mechanical engineering with particular emphasis on: Computational Fluid Dynamics (CFD) modeling of positive displacement machines Screw compressor design, optimization, and performance analysis Grid generation methodologies for complex rotary machinery Thermodynamic analysis of fluid systems Experimental validation of computational models His extensive publication record demonstrates consistent research productivity, with recent work focusing on advanced optimization techniques including Gaussian process regression and Bayesian methods applied to multi-stage screw compressors. His research shows a clear evolution from fundamental CFD modeling to increasingly sophisticated performance optimization and lifecycle cost analysis, with applications across multiple industries including HVAC, refrigeration, and industrial compression systems. Dr. Kovacevic has received recognition for his contributions to the field of positive displacement machinery, with numerous collaborations spanning academic institutions and industrial partners. His work has practical applications in energy-efficient compressor design and optimization, contributing to advancements in sustainable engineering solutions. Throughout his career, Dr. Kovacevic has mentored numerous researchers and students, many of whom have gone on to contribute to the field of mechanical engineering and fluid dynamics. His research has been supported by various grants enabling both fundamental and applied investigations into compressor technology. His laboratory work focuses on the development and validation of advanced CFD models for positive displacement machinery, combining computational approaches with experimental techniques such as Particle Image Velocimetry and infrared thermography for comprehensive system analysis.

• Scientific Computing
• Applied Mathematics
• Parallel Computing
• +3 more

Prof. Dr. Carsten Burstedde is a faculty member at the Institut für Numerische Simulation within the University of Bonn , specifically affiliated with the Faculty of Mathematics and Natural Sciences . His work focuses on developing scalable algorithms for adaptive mesh refinement (AMR) that operate efficiently on the world’s largest supercomputers. He leads the development of the p4est software library , a foundational tool for parallel AMR applications, and contributes to projects like ForestClaw for simulating volcanic ash transport in atmospheric flows. His research spans scientific computing , applied mathematics , and high-performance computing . Key application areas include geophysics (mantle convection, seismic wave propagation), fluid dynamics (incompressible flows, volcanic ash transport), and uncertainty quantification for inverse problems. He emphasizes non-conforming mesh techniques and parallel numerical solutions of PDEs , with a particular interest in hybrid mesh algorithms for complex domains. The 15 most recent publications highlight his expertise in adaptive mesh refinement across diverse contexts: 2021 works on heterogeneous systems and ghost layer optimization , 2020 contributions to p4est software and CPU ray tracing of AMR data, 2019 studies on Morton-type space-filling curves , and 2018–2016 projects enhancing ParFlow and ESPResSo with adaptive methods. Earlier papers (2015–2012) address Bayesian inverse problems , level-set methods , and multi-scale geodynamics . Scientific Awards include the Springer CSE Prize (2011) and the NSF TeraGrid Capability Computing Challenge (2008) . He has advised PhD student Johannes Holke , with whom he developed tetrahedral space-filling curves and hybrid AMR algorithms . His teaching includes courses on scientific computing , adaptive mesh refinement , and mathematics in music . The p4est summer school (2020) and collaboration with Donna Calhoun (ForestClaw project) underscore his leadership in computational science outreach and education.

Pengtao SunView profile

Professor

• Computational Mathematics
• Numerical Solutions of Partial Differential Equations
• Finite Element Method
• +5 more

Pengtao Sun is a Professor in the Department of Mathematical Sciences at the University of Nevada, Las Vegas (UNLV). His research focuses on computational mathematics, numerical solutions of partial differential equations, and scientific computing, with applications in fluid-structure interaction, fuel cell dynamics, and clean energy technologies. Supported by NSF since 2009, his work emphasizes advanced numerical methods like the finite element method, finite volume method, and domain decomposition techniques. He has contributed to modeling fluid-structure interactions using ALE and fictitious domain methods, as well as studies on lithium batteries and PEM fuel cells. His research also explores energy-preserving algorithms and machine learning approaches for complex systems. Dr. Sun’s expertise includes anisotropic/isotropic adaptive finite element methods, phase field methods, and the development of efficient solvers for multiphysics problems. His recent work addresses challenges in deterministic lateral displacement problems and thermal management of energy systems. He collaborates with the Center for Applied Math & Statistics (CAMS) at UNLV and has published extensively on topics like blood pressure prediction via fluid-structure interaction modeling and mesh-free neural network methods. His research portfolio reflects a blend of theoretical advancements and practical applications, bridging computational mathematics with engineering and environmental science. While no awards are explicitly listed, his sustained NSF funding underscores the significance of his work in advancing numerical methodologies for complex physical systems.

Jack KingView profile

Research Fellow

• High-order and mesh-free methods
• Free surface flows and breaking waves
• Reacting flows and combustion technologies
• +3 more

Jack King is a Royal Society University Research Fellow at the University of Manchester's School of Engineering, specializing in Mechanical and Aerospace Engineering. He holds a PhD from the University of Edinburgh and a Bachelor's in Engineering from the University of Cambridge. His research focuses on developing novel numerical methods for complex fluid flows, particularly combustion simulations for clean energy technologies. Key areas include high-order/mesh-free methods (e.g., LABFM/SPH), free surface flows, reacting flows, fluid instabilities, and non-Newtonian fluids. He has been awarded the Dame Kathleen Ollerenshaw Fellowship (2022) and the Royal Society University Research Fellowship (2023). His work spans collaborations in fluid dynamics, with publications addressing viscoelastic flows, breaking waves, and high-order simulations. He is part of the Fluids Research Group, actively involved in projects on turbulent flows and computational fluid dynamics.

• Minerals Processing
• Multiphase Flow Modelling
• Froth Flotation
• +7 more

Professor Stephen Neethling is a distinguished academic at Imperial College London's Department of Earth Science & Engineering, part of the Faculty of Engineering. His research focuses on multiphase flow modeling in minerals processing, particularly heap leaching and froth flotation. He leads the Advanced Mineral Processing Research Group and contributes to the Applied Modelling and Computation Group. Notable achievements include a 2011 Royal Academy of Engineering Senior Research Fellowship. Education: BSc Chemical Engineering (1992–1995), University of Cape Town PhD (1996–1999), UMIST (now part of the University of Manchester) Research Interests: Modelling fluid flow and mass transport in heaps using SPH and FEM/FVM methods Foam/froth dynamics in flotation cells and industrial applications Development of SPH-DEM coupled simulators for multiphase systems Integration of experimental techniques like PEPT and micro-CT for validation Heap leaching optimization through spatiotemporal analysis Articles Trends: Recent work emphasizes heap leaching heterogeneity (2024-2025) SPH-based modeling dominates computational studies Focus on industrial applications like CoarseAIR™ flotation cells Awards: 2011 Senior Research Fellowship, Royal Academy of Engineering Labs/Teams: Advanced Mineral Processing Research Group Applied Modelling and Computation Group Computational Modelling, AI, and Machine Learning Team

Georgios FourtakasView profile

Lecturer

• Meshless Methods
• Computational Fluid Dynamics (CFD)
• Smoothed Particle Hydrodynamics (SPH)
• +5 more

Dr. Georgios Fourtakas is a Lecturer in Civil Engineering at the University of Manchester’s School of Mechanical Aerospace and Civil Engineering. He specializes in meshless methods, computational fluid dynamics (CFD), and smoothed particle hydrodynamics (SPH). His research focuses on advancing SPH formulations for complex fluid-structure interactions, multiphase flows, and high-performance computing (HPC) applications, particularly through the DualSPHysics open-source framework. He holds a PhD from the University of Manchester (2014) and prior industry experience in aeronautical engineering and thermal fluid mechanics. Education: BEng in Aeronautical Engineering, University of Salford MSc in Aeronautical Engineering, Cranfield University MSc in Thermal Power and Fluid Mechanics (Academic Return) PhD in SPH Applications (University of Manchester) Key Research Areas: SPH formulations (Lagrangian, Eulerian-Lagrangian, ALE) GPU/CUDA acceleration for HPC Boundary condition development Non-Newtonian and sediment flows Fluid-structure interaction (e.g., heart valves) His work contributes to UN Sustainable Development Goals through applications in coastal engineering, cardiovascular systems, and nuclear decommissioning. He has reviewed for journals like Advances in Water Resources and Journal of Hydroinformatics . Recent articles highlight innovations in divergence cleaning for SPH, GPU-accelerated thrombus modeling, and poroelasticity simulations. His DualSPHysics project is widely adopted for real-world engineering problems.

Rasool ErfaniView profile

Senior Lecturer

• Plasma Engineering
• Computational Fluid Dynamics
• Environmental Science
• +3 more

Dr. Rasool Erfani is a Senior Lecturer at Manchester Metropolitan University (MMU), leading the Modelling and Digital Twin theme within the Smart Infrastructure & Industry Research (SIIR) Group. His research focuses on plasma engineering, computational fluid dynamics (CFD), and experimental fluid dynamics, with applications in environmental science, healthcare, and resource management. He holds an honorary Associate Professor position at University College London (UCL). Dr. Erfani has secured significant grants, including a £600k NIHR-i4i grant for a vocalisation device for tracheostomised patients and three Innovate UK-KTP grants totaling £550k. These projects address industrial challenges such as leak detection in water systems and SF6-free air quality assessment. Education: PhD in Mechanical Engineering from The University of Manchester, MSc in Applied Fluid Dynamics from The University of Manchester, PGCert in Learning and Teaching (Manchester Met). His research interests span plasma-based technologies for healthcare and environmental applications, renewable energy systems, and advanced flow diagnostics. Notable achievements include the IMechE Andrew Medd Award (2020) and the Institute of Water Innovation Award (2020). Key collaborations: NHS, Severn Trent Water, Motherwell Tank, Clean Air, and Lb Orthopaedics Manchester Ltd. Dr. Erfani supervises PhD projects in water/wastewater treatment and medical device development, supported by funding from international organizations. His work emphasizes interdisciplinary innovation, bridging engineering with healthcare and environmental sustainability.

Axel KlarView profile

Professor

• Kinetic Theory
• Traffic Flow Modeling
• Pedestrian Dynamics
• +6 more

Prof. Axel Klar is a Professor in the Department of Technomathematics at the Rheinland-Palatinate University of Applied Sciences (RPTU) Kaiserslautern-Landau. His research focuses on mathematical modeling of complex systems, with a strong emphasis on kinetic theory, fluid dynamics, and applied analysis. Key areas of expertise include traffic flow dynamics, fiber dynamics in industrial processes, pedestrian movement patterns, and biological systems such as cell motion and tumor growth. He develops and analyzes numerical methods for partial differential equations and stochastic systems, often addressing challenges in technical textile production, non-equilibrium thermodynamics, and multi-physics simulations. His work bridges microscopic particle-based models with macroscopic continuum descriptions, emphasizing asymptotic methods and domain decomposition techniques. Notable contributions include stochastic fiber lay-down models for nonwoven manufacturing, mesh-free particle methods for granular and rarefied gas flows, and kinetic-based traffic models with applications to autonomous vehicles and crowd control. Current research explores data-driven approaches for coupled systems in socio-economic and biomedical contexts. Prof. Klar’s interdisciplinary projects involve collaborations with industry partners (e.g., in textile engineering) and academic institutions globally. His team develops open-source numerical toolkits for applications ranging from radiation therapy optimization to climate-resilient infrastructure design. Recent efforts focus on AI-driven parameter estimation for high-dimensional PDE systems and uncertainty quantification in multi-scale modeling.

Jens StruckmeierView profile

Professor

• Numerical Analysis
• Computational Fluid Dynamics
• Kinetic Theory
• +3 more

Prof. Jens Struckmeier is a faculty member at the University of Hamburg, holding the position of Professor of Numerics within the Department of Mathematics, Faculty of Mathematics, Computer Science and Natural Sciences. His research focuses on applied mathematics, particularly numerical methods for partial differential equations, computational fluid dynamics, kinetic theory, and optimal control. He has contributed extensively to areas such as particle methods for the Boltzmann equation, finite-volume particle methods for conservation laws, and mathematical modeling of crystallization processes and thermal flows. His work often bridges theoretical developments with industrial applications, such as fire simulations in vehicle tunnels and polymer crystallization studies. Struckmeier's research interests include numerical analysis, kinetic theory, and the development of efficient algorithms for complex systems. He has authored or co-authored numerous publications, including books on hyperbolic partial differential equations and articles in journals like Journal of Computational Physics and Mathematical Models and Methods in Applied Sciences . His work on radiation models for low Mach number flows and optimal control of crystallization processes demonstrates interdisciplinary applications of mathematical modeling. Notable contributions include the finite-volume particle method for moving domains and kinetic schemes for granular flow equations (Savage-Hutter equations). He collaborates widely, with co-authors across institutions, and his research often addresses real-world challenges in engineering and physics. While no specific awards are listed, his sustained academic output reflects significant contributions to numerical mathematics and applied sciences.

Natalie BeamsView profile

Academic

• High-Performance Computing
• Scientific Computing
• Numerical Methods for PDEs
• +3 more

Natalie Beams is a Research Assistant Professor at the Innovative Computing Laboratory (ICL) within the University of Tennessee's Department of Electrical Engineering and Computer Science (EECS). She holds a PhD in Theoretical and Applied Mechanics from the University of Illinois at Urbana-Champaign (UIUC), an MS from UIUC, and a BS in Mechanical Engineering (summa cum laude) from the University of Oklahoma. Her research focuses on numerical methods for PDEs, high-performance computing (HPC), and GPU-accelerated algorithms, with contributions to projects like the Exascale Computing Project's CEED and CLOVER initiatives. Key research areas include finite element methods , integral equation solvers , and mixed-precision algebraic multigrid techniques . She has developed software tools such as the libCEED library for high-order discretizations and contributed to the Ginkgo and MAGMA libraries. Her work emphasizes exascale computing, GPU optimization, and parallel algorithm design. Education: PhD in Theoretical & Applied Mechanics, UIUC (2017) MS in Theoretical & Applied Mechanics, UIUC (2014) BS in Mechanical Engineering, University of Oklahoma (2010) Awards & Honors: Best Workshops Paper Award, PPAM Conference (2022) 2011/2012 Computational Science & Engineering Fellow 2010 College of Engineering Carver Fellow List of Teachers Ranked as Excellent by Students (UIUC, 2014) Grants & Projects: Active contributor to the Exascale Computing Project (ECP), leading efforts in CEED (libCEED library) and CLOVER (MFEM-Ginkgo interoperability). Collaborates with Rice University and other institutions on HPC and numerical algorithms. Labs & Teams: Core member of the Innovative Computing Laboratory (ICL) at UTK, specializing in exascale software and GPU-accelerated computing.

• Geomechanics
• Granular Materials
• Computational Mechanics
• +3 more

Dr. Yucheng Li is a researcher at the Institute of Geomechanics and Underground Technology (GUT) within the Faculty of Civil Engineering at RWTH Aachen University, specializing in computational analysis of granular material behavior under geotechnical conditions. His research focuses on granular column collapse dynamics , examining critical parameters including gravity variations , basal friction effects , and numerical modeling techniques . He employs advanced computational methods such as Smoothed Particle Hydrodynamics (SPH) to simulate granular flows, with applications in landslide prediction and geotechnical structure design. Key research areas include soil mechanics, granular physics, and computational geomechanics. Recent publications reveal a strong emphasis on environmental parameter effects in granular collapse phenomena, particularly gravity-level dependencies and boundary condition influences. This work bridges experimental geomechanics with high-fidelity numerical simulation, contributing to hazard assessment methodologies in unstable terrain.

• Computer Graphics
• Physics-Based Simulation
• Fluid Dynamics
• +3 more

Prof. Dr. Jan Bender holds a professorship in Computer Animation at RWTH Aachen University's College of Engineering. As a leading researcher in physics-based simulation methods, his work focuses on developing advanced numerical techniques for fluid dynamics, deformable solids, and multi-physics interactions through Smoothed Particle Hydrodynamics (SPH) and Finite Element Methods (FEM). Key Contributions: Invented PF-FLIP for two-phase flows, developed SymX symbolic framework for energy-based simulations, created STARK unified solver for robotics applications, and introduced implicit boundary handling for SPH Methodologies: Specializes in hybrid Eulerian/Lagrangian approaches, differentiable physics, adaptive discretization, and machine learning integration for simulation acceleration Research Impact: 2023 & 2024 Best Paper Awards in VMV and SCA conferences. His work enables billion-particle fluid simulations and realistic multi-body interactions for robotics, with applications in welding, thermal spraying, and soft robotics. Collaborations: Works extensively with robotics institutes (Gazebo Fluids extension) and materials science departments (TIG welding, thermal spray modeling). Maintains open-source code repositories for simulation frameworks.

• Numerical Analysis
• Computational Mechanics
• Phase-field Modeling
• +3 more

Prof. Dr. Carsten Gräser is a Professor in the Department of Applied Mathematics at Friedrich-Alexander University Erlangen-Nürnberg (FAU). His research focuses on numerical analysis, computational mechanics, and phase-field modeling, with an emphasis on nonsmooth optimization and multigrid methods for complex systems. 2025: Well-posedness of evaporation models for droplets. 2023: Multiscale fault systems and phase-field brittle fracture simulations. 2021: Membrane mechanics and DUNE framework developments. His work spans partial differential equations, computational geosciences, and biological membrane modeling, often involving finite element methods and nonlinear systems. Recent publications highlight applications in fluid dynamics, fracture mechanics, and geophysical fault simulation. His articles demonstrate a strong focus on numerical methods for phase-field models and nonsmooth systems, with recurring sub-fields like multigrid algorithms, membrane-mediated interactions, and finite element discretization. He collaborates widely on topics such as marine ice sheets and solder alloy coarsening. At FAU, Gräser teaches courses including Numerics of Incompressible Flows and Modeling, Simulation, and Optimization . His research integrates software development (e.g., the DUNE framework) with applications in physics, materials science, and geosciences.

Doug CleaverView profile

Professor

• Molecular Modelling
• Materials Science
• Soft Matter Physics
• +3 more

Doug Cleaver is a Professor of Materials Modelling and Director of the Doctoral School at Sheffield Hallam University. He has been with the institution since 1994, following postdoctoral work in Chemistry at Southampton. His academic roles include leading doctoral programs and supervising over 20 completed PhDs. He holds a Personal Chair since 2009 and received the 2012 Cyril Hilsum Medal for contributions to liquid crystal research. Research interests focus on molecular and mesoscopic modeling of soft matter systems, including liquid crystals, self-assembling nanostructures, and computational techniques like molecular dynamics and lattice Boltzmann methods. Key projects involve hierarchical fiber assembly, clay-polymer composites, and supramolecular gyroid structures. Collaborations span international partners such as CCP5 and STFC Daresbury Laboratory. Publications emphasize novel simulation approaches, with over 50 papers and 1000 citations. Recent work includes studies on oblate particle confinement, gyroid phase formation, and pear-shaped colloids. Awards include the Cyril Hilsum Medal (2012) for mid-career contributions to liquid crystal science. Grants: EPSRC, EU FP7, and industrial partners (HP, Rolls Royce). Outreach: Public lectures and simulations for the Soft Matter World initiative. External examiner for over 20 PhDs globally. Labs/Teams: Active in STFC Daresbury’s DL_POLY simulations and international collaborations on soft matter systems.