Find Academic Supervisors

• Computational Methods
• High Performance Computing
• Cloud Computing
• +3 more

Professor Simon Cox is a Professor of Computational Methods and Director of the Microsoft Institute for High Performance Computing within the Faculty of Engineering and Physical Sciences at the University of Southampton. He holds a doctorate in Electronics and Computer Science, complemented by first-class degrees in Mathematics and Physics. His research focuses on computational tools and platforms, particularly in high-performance computing, cloud computing, and interdisciplinary applications in engineering and science. He has secured over £30 million in research and enterprise funding, published over 250 papers, and is a Microsoft Most Valuable Professional since 2003. Research interests include computational electromagnetics, meshless methods, and data management. His team, the Computational Engineering and Design Group, develops high-performance computing systems and commercial distributed computing solutions. Notable projects include a Raspberry Pi and Lego-based supercomputer and a spin-off company from computational electromagnetics research. He actively supervises PhD students in Engineering and Environmental Science. Key awards include the Microsoft MVP title. His work spans environmental monitoring (e.g., methane sensors, IoT-based peatland tracking), cybersecurity for IoT devices, and biomedical applications like 3D X-ray histology. He leads outreach initiatives, including the 'Supercomputing in Engineering Course' since 2005.

Hoang Xuan PhuView profile

Professor

• Optimization
• Optimal Control
• Functional Analysis
• +6 more

Professor Hoang Xuan Phu is a renowned mathematician affiliated with the Institute of Mathematics , Vietnam Academy of Science and Technology , where he has served since 1984 (Researcher), 1992 (Associate Professor), and 1996 (Professor). He is an elected member of multiple prestigious academies: the Heidelberg Academy of Sciences and Humanities (2004), Bavarian Academy of Sciences and Humanities (2010), TWAS - The World Academy of Sciences (2013), and acatech - National Academy of Science and Engineering, Germany (2019). His email contact is hxphu@math.ac.vn and phu@iwr.uni-heidelberg.de . Education : University of Leipzig (Diploma 1979, PhD 1983, Habilitation 1987) Research Areas : Optimization, Optimal Control, Functional Analysis, Numerical Analysis, Rough Analysis Applications : Inventory Problems, Hydroelectric Power Plant Control, Robotics, Open Channel Hydraulics Editorial Roles : Editor-in-Chief of Vietnam Journal of Mathematics (2011-2022), Honorary Editor-in-Chief (2023-present), Associate Editor for multiple journals His recent publications focus on convex hull algorithms, optimal path planning, and function perturbation analysis, reflecting his expertise in mathematical optimization and computational methods. He has organized numerous international conferences on High Performance Scientific Computing in Hanoi (2000-2024) and Optimization & Scientific Computing (2003-2024).

Shiqiang YanView profile

Professor

• Wave/current/wind interaction
• Structure responses in extreme sea conditions
• Renewable energy and low carbon technologies
• +2 more

Professor Shiqiang Yan is an ocean engineering expert at City St George's, University of London , with over 25 years of academic experience. He obtained his PhD in Hydraulics (2007) from City University London, following MSc (2004) and BEng (1999) from Dalian Maritime University. His career includes Postdoctoral Research Fellow (2007-2012) and Lecturer (2012–present) positions at City University. Specializes in Wave-Structure Interaction and Extreme Sea Condition Modeling Developed QALE-FEM and ISPH-GNN hybrid numerical methods Research spans Wave Energy , Offshore Wind , and Marine Pollution Control His 15 most recent publications (2021-2025) demonstrate expertise in Wave-Structure Interaction (40% of articles), Hybrid Modeling (30%), and Renewable Energy Systems (25%). Key subfields include Wave-WEC Coupling , Ice Floe Dynamics , and Multi-Scale Hydrodynamic Modeling . He has advised PhD student Hao Yang (2013–present) on submerged oil spill research. Professional memberships include the International Society of Ocean & Polar Engineering (2013–present).

Uday BanerjeeView profile

Professor

• Numerical Analysis
• Partial Differential Equations
• Finite Element Methods
• +3 more

Uday Banerjee is a Professor in the Department of Mathematics at Syracuse University, affiliated with the College of Arts & Sciences. His research focuses on numerical solutions of elliptic PDEs, particularly using finite element methods, meshless methods, and generalized finite element techniques to address non-smooth coefficients and interface problems. He holds a Ph.D. in Applied Mathematics from the University of Maryland (1985), an M.Sc. from the Indian Institute of Technology (1978), and a B.Sc. from Patna University (1975). His recent work emphasizes approximation properties, error estimation, and implementation challenges in numerical methods. Key contributions include penalty-free SGFEM for interface problems and stable generalized FEM for crack analysis. Banerjee has served as Chair of the Department of Mathematics (2014–2020) and holds roles in university governance, including serving on promotion and tenure committees. He teaches courses like MAT 331 (Linear Algebra) and MAT 581 (Numerical Methods).

• Computational Mechanics
• Biomechanics
• Mechanical and Material Engineering
• +3 more

Professor YuanTong Gu is the Pro Vice-Chancellor (Research Career Advancement) and Head of the School of Mechanical, Medical and Process Engineering at Queensland University of Technology (QUT). He holds an ARC Future Fellowship and leads the Laboratory for Advanced Modelling and Simulation in Engineering and Science. His research focuses on computational mechanics, biomechanics, and nanotechnology, with over $40M in secured research funding since 2000. He has supervised over 15 PhD students and collaborates with global institutions including Tsinghua University and the University of California. His awards include the International Computational Methods Award (2017) and ICACM Computational Mechanics Award (2017). Prof. Gu's work spans interdisciplinary projects in joint biomechanics, advanced materials, and AI-driven engineering solutions. Education: PhD (National University of Singapore), Graduate Certificate in Education (QUT). Research Groups: Leads a team of 3 academics, 2 ARC Future Fellows, and 15+ PhD students. Key projects include diamond nanothread composites, AI in biomedical devices, and fracture detection frameworks. His group collaborates with industry leaders and global universities to advance computational methods and materials science. Editorial Roles: Associate Editor of Engineering Analysis with Boundary Elements and Applied Mathematical Modelling , among others. Conference leadership includes chair roles in international computational mechanics conferences since 2012.

Fayssal BenkhaldounView profile

Professor

• Finite Volume Methods
• Computational Fluid Dynamics
• Shallow Water Equations
• +3 more

Fayssal Benkhaldoun is a Professor at Université Paris 13, affiliated with the LAGA laboratory (UMR7539). He has held leadership roles including former Head of the MCS team (Modeling and Scientific Computing) at LAGA and former President of the Scientific Council at IUT Villetaneuse. He is also the Project Leader of the International Office at IUT Villetaneuse. His research focuses on numerical methods for partial differential equations, particularly finite volume schemes for hyperbolic and elliptic problems. Key areas include shallow water equations, flow in porous media, mesh adaptation, and combustion front propagation. He has organized major conferences such as the International Symposium on Finite Volumes for Complex Applications (FVCA), initiating its first edition in 1996. Recent work emphasizes advanced numerical techniques like stabilized meshless methods, GPU acceleration, and parallel computing for CFD applications. His contributions span environmental modeling (flood simulation, sediment transport) and industrial applications (phosphate slurry rheology). Students advised include Jan Karel (2014, streamer propagation) and Saida Sari (2013, multilayer shallow water equations). He co-organized conferences since 1996 and has been an invited speaker at numerous institutions globally.

James CampbellView profile

Professor

• Numerical Modelling
• Impact Engineering
• Crashworthiness
• +4 more

Dr James Campbell is a Reader in Structural Integrity at Brunel University London's Department of Mechanical and Aerospace Engineering within the College of Engineering, Design and Physical Sciences. With a PhD in hypervelocity impact on spacecraft and 20+ years of experience leading multidisciplinary projects, he specializes in non-linear numerical methods (FE and SPH), structural integrity, and impact analysis across aerospace, defense, and automotive sectors. BEng in Aeronautical Engineering, Imperial College London MSc and PhD in Astronautics and Space Engineering, Cranfield University His research focuses on: Transient response of materials/structures (e.g., space debris impact, aircraft crashworthiness) Meshless methods like Smoothed Particle Hydrodynamics (SPH) Constitutive models for isotropic/orthotropic materials Fluid-structure interaction in ditching and extreme wave events Recent work trends include space debris removal tools, composite material development for offshore energy, and advanced SPH algorithms for impact simulations. Awards include the Derek George Astridge Safety in Aerospace Award (2009) and Royal Institute of Naval Architects Medal (2010). He supervises PhD/MSc students and delivers CPD courses for industry (Boeing, Leonardo). Research group: IMM (International Marine and Offshore). Collaborations include Airbus, DLR, and ESA.

• Applied Analysis
• Numerical Analysis
• Data Science
• +6 more

Leon Bungert is a Professor of Mathematics of Machine Learning at the University of Würzburg, working in applied analysis and numerics with a particular focus on data science and machine learning. His research investigates PDEs and variational models on graphs, adversarial robustness of machine learning, variational regularization, and nonlinear optimization. Dr. Bungert serves as a guest editor for the European Journal of Applied Mathematics, an associate editor for Advances in Continuous and Discrete Models: Theory and Applications, and is a member of the program committee at SSVM 2025. He is also an ELLIS member and actively organizes conferences and workshops, including "MIA'25" at IHP in Paris (January 13-15, 2025), "Synergies of Machine Learning and Numerics" in Osaka (March 11-13, 2025), and "Mathematical Analysis of Adversarial Machine Learning" in Oaxaca (August 17-22, 2025). Research Interests Dr. Bungert's primary research areas include: PDEs on graphs Adversarial robustness in machine learning Inverse problems Optimization Variational problems in L-infinity Nonlinear eigenvalue problems Image reconstruction with structural priors His work bridges theoretical mathematics with practical applications in machine learning, particularly focusing on the mathematical foundations of deep learning and developing robust algorithms that can withstand adversarial attacks. He has made significant contributions to understanding the connections between partial differential equations and machine learning algorithms. Research Trends Analysis of Dr. Bungert's recent publications reveals a strong focus on the intersection of machine learning and mathematical analysis. A key theme is the application of variational methods and partial differential equations to machine learning problems, particularly in understanding and improving the robustness of neural networks against adversarial examples. His work on Lipschitz learning on graphs has established important theoretical foundations for graph-based semi-supervised learning. Additionally, his research on the infinity Laplacian and p-Laplacian equations provides deep insights into the mathematical structure of machine learning algorithms. The development of Bregman learning frameworks for sparse neural networks represents a significant contribution to efficient deep learning model training. Professional Activities Dr. Bungert is actively involved in the academic community through editorial roles and conference organization. His current professional activities include: Guest editor for the European Journal of Applied Mathematics Associate editor for Advances in Continuous and Discrete Models: Theory and Applications Member of the program committee at SSVM 2025 ELLIS member Co-organizer of multiple international conferences and workshops Technical Contributions Dr. Bungert has developed several open-source software packages that implement his theoretical contributions, including: Code for convergence rates of Lipschitz learning on graphs A Bregman training framework for sparse neural networks CLIP: Cheap Lipschitz Training of Neural Networks Nonlinear Power Method for Proximal Operators and Neural Networks Robust Image Reconstruction with Misaligned Structural Information These implementations are primarily in Python and MATLAB, demonstrating his commitment to making theoretical advances accessible for practical applications.

Thibault TricardView profile

Associate Professor

• Computer Graphics
• Procedural Modeling
• 3D Printing
• +5 more

Thibault Tricard is an Associate Professor at Ensimag Grenoble and a permanent researcher in the Maverick team at Inria Grenoble. His work bridges Computer Graphics and Additive Manufacturing , focusing on procedural methods for virtual world content generation. His research interests include: Procedural modeling for surface and microstructure details Mesh shaders and GPU-accelerated volume rendering 3D printing optimization with staggered infill structures Recent publications like Interval Shading (HPG 2024) and Procedural Phasor Noise (ACM Siggraph 2020) highlight trends in real-time rendering and fabrication-aware procedural synthesis. Awards include the GDR IG-RV Thesis Award 2023 . He advises PhD students and collaborates with researchers such as Sylvain Lefebvre and Hans-Peter Seidel. Teaching includes GP-GPU High-Performance Computing and 3D Graphics at Inp Grenoble and UGA Mosig. Personal projects like the LavaCake Vulkan library emphasize developer accessibility.

Amirreza KhodadadianView profile

Lecturer

• Uncertainty Quantification
• Numerical Analysis
• Computational Mechanics
• +7 more

Dr. Amirreza Khodadadian is a Lecturer in Mathematics at the School of Computer Science and Mathematics, Keele University, since August 2023. He holds a Ph.D. from the University of Vienna (2017), followed by postdoctoral positions at the Technical University of Vienna and Leibniz University Hannover. His research focuses on uncertainty quantification, numerical methods for stochastic PDEs, finite element methods, computational mechanics, and machine learning applications in nanoelectronics and biological systems. Key research interests include Bayesian inversion, multiscale modeling, reduced-order methods, and the design of nanoscale sensors. He has collaborated with institutions like the University of Oxford and secured an Austrian Science Fund (FWF) grant (476k€) for nanozyme sensor research. Dr. Khodadadian mentors postdoctoral researchers, including Dr. Samaneh Mirsian, and actively publishes in top-tier journals such as Journal of Computational Physics and Computer Methods in Applied Mechanics and Engineering . His work bridges applied mathematics with engineering challenges, emphasizing efficient numerical algorithms for real-world problems like battery degradation, groundwater contamination, and biomedical sensor optimization. Recent projects involve machine learning integration for enhanced predictive modeling. Education: Ph.D. in Mathematics, University of Vienna, Austria (2017) Postdoctoral Fellowships: TU Vienna (2018), Leibniz University Hannover (2018–2022) Grants/Awards: Austrian Science Fund (FWF) Grant: Single Atom Catalysts as Nanozymes in FET Sensors (2023) Advising: Postdoctoral Mentor: Dr. Samaneh Mirsian (Keele University) Dr. Khodadadian’s publications span computational mechanics, stochastic modeling, and interdisciplinary applications, reflecting his expertise in translating mathematical theory into practical engineering solutions.

Stéphane BORDASView profile

Professor

• Computational Mechanics
• Biomechanics
• Finite Element Methods
• +6 more

Stéphane BORDAS is a Full Professor in Computational Mechanics at the University of Luxembourg's Faculty of Science, Technology and Medicine (FSTM), leading the Computational Mechanics (Legato) research group. His work focuses on free boundary problems, method development for complex geometries, and applications in fracture mechanics, biomechanics, and computational engineering. He previously held roles at Cardiff University and the Swiss Federal Institute of Technology in Lausanne (EPFL). His research integrates computational methods like XFEM, isogeometric analysis, and meshfree techniques to address challenges in engineering and medicine. Education: Ph.D. in Theoretical and Applied Mechanics, Northwestern University (2003) M.Sc. in Civil Engineering, École Spéciale des Travaux Publics and Northwestern University (1999) Research Interests: Computational Mechanics, Biomechanics, Finite Element Methods, Fracture Mechanics, High-Performance Computing, Isogeometric Analysis. Grants & Projects: ERC Starting Grant (RealTCut) for surgical simulation and material cutting FP7 ITN INSIST for meshless methods Labs/Teams: Computational Mechanics (Legato) Group at the University of Luxembourg. His work bridges academia and industry, with applications in aerospace, biomedical engineering, and materials science. He is active in open-source software development, including codes for XFEM, isogeometric analysis, and meshfree methods.

Hans-Peter SeidelView profile

Professor

• Computer Graphics
• 3D Image Analysis
• Digital Geometry Processing
• +3 more

Hans-Peter Seidel is a leading academic in computer graphics, serving as Director of the Max Planck Institute for Informatics and Full Professor at Saarland University since 1999. Previously held roles include Full Professor at University of Erlangen (1992–1999) and Assistant Professor at University of Waterloo (1989–1992). Holds a PhD in Mathematics (1987) and Habilitation in Informatics (1989) from University of Tübingen. Research focuses on 3D image analysis, digital geometry processing, visual computing, and free viewpoint rendering. Key achievements include pioneering work in surface editing, motion capture, and multi-view video processing. Has organized major conferences like Eurographics and SIGGRAPH, serving as editor for journals including IEEE TVCG and Computer Aided Geometric Design. Recipient of the Eurographics Distinguished Career Award (2012), Gottfried Wilhelm Leibniz Prize (2003), and numerous fellowships. Led initiatives such as the Cluster of Excellence on Multimodal Computing and Interaction (M2CI) and the Max Planck Center for Visual Computing and Communication (MPC-VCC). Active in academic leadership roles including Eurographics Chair and DFG committees. Publications span over 30 SIGGRAPH and 50 Eurographics contributions, with an h-index of 62 and 14,000+ citations. Recognized as a top-cited researcher in computer graphics. Current research explores advanced visualization techniques and geometric modeling innovations.

• Cardiac Flow Dynamics
• Echocardiography
• Biomedical Engineering
• +3 more

Brett Meyers is an Assistant Research Professor at Purdue University's College of Engineering, specializing in biomedical engineering and cardiovascular fluid dynamics. His research focuses on advancing echocardiographic techniques, computational fluid dynamics (CFD), and medical imaging technologies to assess cardiac function in patients with congenital heart defects, sepsis, and other cardiovascular conditions. Key contributions include developing the Doppler Velocity Reconstruction (DoVeR) method and enhancing fetal/neonatal echocardiography for early diagnosis. Education details are not explicitly stated in the provided text. His work spans pediatric cardiology, adult heart failure, and biomaterials, with a strong emphasis on translational research. Meyers has pioneered methods to quantify intracardiac flow patterns using 4D flow MRI and ultrasound-based techniques like EchoPIV (Echocardiographic Particle Image Velocimetry). Research interests include hemodynamic biomarker development for sepsis prognostication, single ventricle heart biomechanics, and fluid mechanics in biological systems (e.g., snake tongue flicking). He has authored over 50 peer-reviewed articles since 2013, with recent work focusing on AI-driven analysis of echocardiograms and novel drug delivery systems using synchrotron imaging. While no specific awards are listed, his innovative methodologies have been applied in clinical settings, such as assessing exercise capacity in repaired Tetralogy of Fallot patients and refining therapeutic regimens for thrombotic disorders. Meyers collaborates with multidisciplinary teams in Purdue's biomedical engineering and mechanical engineering departments, contributing to both academic and industrial partnerships.

Xiaozhe HuView profile

Professor

• Scientific Computing
• Numerical Analysis
• Multigrid Methods
• +7 more

Xiaozhe Hu is a full-time Professor in the Department of Mathematics at Tufts University since July 2024. Previously held positions include Associate Professor (2019-2024) and Assistant Professor (2014-2019) at Tufts, and Adjunct Associate Professor (2020-2022) at the University of Bergen, Norway. Education : PhD in Computational Mathematics (Zhejiang University, 2009); BS in Information and Computer Science (Zhejiang University, 2004) His research focuses on scientific computing and numerical analysis , particularly: Development of adaptive and parallel numerical methods for PDEs and graph problems Multigrid/multilevel solvers for large-scale coupled systems Quantum algorithms and spectral graph theory Applications in poromechanics , reservoir simulation , and bioinformatics Recent publications demonstrate expertise in preconditioning techniques for Biot’s model, meshless methods for fluid-structure interaction, and data-driven discretization approaches . Awards include the Reimann-Louville Award (2016) and outstanding PhD graduate recognition (Zhejiang Province, 2009). PhD Students : Junyuan Lin (Loyola Marymount), Peter Ohm (RIKEN), Casey Cavanaugh (LSU), Kaiyi Wu, Eoghan O'Keefe Master Students : Charles Colley (Purdue PhD), Yue Shen (Florida State PhD), Samuel Rabinowitz, Phong Huang, Samuel Hocking Co-organizer of the Computational and Applied Mathematics Seminar and contributor to open-source HAZmath finite element library.

• Fluid Dynamics
• Computational Fluid Dynamics
• Biofluids Flow
• +6 more

Vassilios Loukopoulos is a Professor at the Department of Physics, University of Patras, Greece. He has held academic positions including Lecturer (2007), Assistant Professor (2011), Associate Professor (2016), and Professor (2021). His research focuses on Fluid Dynamics, Computational Fluid Dynamics, and interdisciplinary applications in biofluids, nanofluids, and magnetohydrodynamics. Education: BSc, MSc, and PhD in Physics from the University of Patras (1993–2001) Research Interests: His work spans theoretical and numerical studies of fluid mechanics, with applications to cardiovascular flows, blood rheology, heat transfer enhancement using nanofluids, microfluidics, porous media, and high-performance computing. He has contributed to modeling MHD flows, biofluid dynamics, and computational methods for nonlinear PDEs. Publications & Collaborations: He has authored over 80 articles in top journals with 1040 citations. His collaborations include institutions like Max Planck Institute (Germany), KAUST (Saudi Arabia), EPFL (Switzerland), and the Institute of Chemical Engineering Sciences (Greece). Recent work highlights meshless numerical methods for fluid dynamics and biomedical applications. Scientific Contributions: He serves as a referee for 28 international journals and is on the editorial board of Mathematical Problems in Engineering . He has participated in 5 European/national research projects and authored 5 academic books.