Shock-capturing algorithms Professors and Supervisors

Fideline Tchuenbou-Magaiaمشاهده پروفایل

مدرس ارشد

University of WolverhamptonUnited Kingdom

Dr. Fideline Tchuenbou-Magaia is a Reader in Green Technology at the University of Wolverhampton’s School of Engineering, Faculty of Science and Engineering. She is a multidisciplinary scientist with expertise bridging Chemical Engineering, Biochemistry, and Formulation Science. Her academic journey includes a PhD in Chemical Engineering from the University of Birmingham (2012), a Master’s in Food Science and Technology from Agro ParisTech (2006), and a BSc in Biochemistry from the University of Douala (2001). Key research areas: Sustainable formulation engineering, Cold energy storage, Carbon capture, and IoT applications in agriculture Leading Energy and Green Technologies Research Group Active in product development for industry (Nestle, PepsiCo, Micreos) Publications span waste valorisation, smart packaging, battery systems, and sustainable agriculture. Notable grants include £934,275 EPSRC funding for cold energy storage (2015–2019) and over £1 million in Innovate UK/EU energy projects since 2015. Awards include: Nominated for 2021 Vice-Chancellor's Awards Student Union Teaching Awards (2020, 2021) Lecturer of the Year (2020) She supervises doctoral students in topics ranging from Metal Organic Frameworks for carbon capture to Smart packaging and battery safety , and serves as External Examiner at multiple UK universities. Her work integrates food, energy, and environmental systems toward a circular economy.

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Vicente Fco Candela Pomaresمشاهده پروفایل

دانشیار

University of ValenciaSpain

Vicente Fco Candela Pomares is an Associate Professor in the Department of Mathematics at the Faculty of Mathematics, University of Valencia, Spain. His academic career has been centered on numerical analysis and computational mathematics, with a focus on iterative methods for nonlinear equations and multiresolution techniques. His research interests lie primarily in Numerical Analysis , especially iterative root-finding methods such as Halley, Chebyshev, and Steffensen-type algorithms. He has contributed significantly to the convergence analysis of these methods, particularly in Banach spaces and for ill-conditioned problems. His work extends to multiresolution analysis , wavelets , and image restoration , where he applies fractional regularization and nonlinear approximation frameworks. The trends in his recent publications show a sustained focus on derivative-free iterative methods , convergence theory , and applications in image processing . His work often bridges theoretical numerical analysis with practical computational challenges. He earned his PhD from the University of Valencia in 1988 under the supervision of Dr. Antonio Marquina Vila, with a thesis on a priori error estimators for iterative methods. He has collaborated extensively with researchers including Sergio Amat, Sonia Busquier, and Rosa Peris. Notable co-authors include Pantaleón D. Romero and Francesc Aràndiga. His publications appear in high-quality journals such as Journal of Computational and Applied Mathematics , Applied Mathematics and Computation , and SIAM journals. He is actively affiliated with the University of Valencia, as evidenced by his institutional email and ongoing publications. There is no indication of part-time status, retirement, or awards in the available data.

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MIGUEL ANGEL ALOY TORASمشاهده پروفایل

استاد

University of ValenciaSpain

Miguel Ángel Aloy Torás is a Professor in the Department of Astronomy and Astrophysics at the Faculty of Physics, University of Valencia. He is a leading researcher in theoretical and computational astrophysics, focusing on high-energy phenomena such as relativistic jets, gamma-ray bursts, and core-collapse supernovae. His research interests span astrophysics, relativistic hydrodynamics, computational physics, and numerical analysis. He specializes in modeling extreme astrophysical environments using advanced numerical simulations, particularly in general relativistic magnetohydrodynamics (GRMHD) and high-performance computing. His work contributes to understanding gravitational wave sources and transient cosmic events. The publications highlight a strong trend in developing and applying numerical methods to solve complex systems in relativistic astrophysics. Early work focused on relativistic hydrodynamics and Riemann solvers, while more recent contributions include algorithmic improvements in iterative solvers like the Scheduled Relaxation Jacobi method, demonstrating a sustained focus on computational innovation for physical modeling. He is the principal investigator of the CAMAP (Computer Aided Modeling of Astrophysical Plasma) research group, which develops simulation codes for astrophysical plasmas. His collaborative network includes prominent researchers in computational astrophysics across Spain and Europe.

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In Young Minمشاهده پروفایل

مدرس

Heidelberg UniversityGermany

In Young Min is a Lecturer in Korean studies at the Centre for East Asian Studies, Heidelberg University. He holds a B.A. and M.A. in Political Science from Yonsei University (South Korea), and a Ph.D. in Political Science and International Relations from the University of Southern California. His research focuses on international relations and security in East Asia, particularly the dynamics of power asymmetry and smaller states' agency in shaping these dynamics, with a regional focus on Korea. Recent work examines historical and contemporary issues surrounding the Korean Peninsula, including nuclear policy and unification treaties. His interdisciplinary contributions span political theory and historical analysis. Education History: B.A. and M.A. in Political Science, Yonsei University, South Korea Ph.D. in Political Science and International Relations, University of Southern California Research Interests: Power asymmetry dynamics in international relations Ontological security and identity in hierarchical systems Korean Peninsula security and unification South Korea's nuclear policy and non-proliferation challenges Publications Trends: His work bridges historical and contemporary analyses, with contributions to journals like the International Relations of the Asia-Pacific and Journal of Asian Security and International Affairs . Earlier technical articles in mathematics and computational methods reflect interdisciplinary engagement, though recent focus is on political science and international relations.

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Yulong Xingمشاهده پروفایل

استاد

Ohio State UniversityUnited States

Yulong Xing is a Professor and Vice Chair for Graduate Studies in the Department of Mathematics at The Ohio State University. His research focuses on numerical analysis and scientific computing, particularly in high-order numerical methods for partial differential equations, computational fluid dynamics, and multiscale modeling. He holds a PhD from Brown University (2006) and has authored numerous papers on discontinuous Galerkin methods, well-balanced schemes, and computational approaches for fluid dynamics and geophysical flows. Key research areas include: Discontinuous Galerkin (DG) methods for hyperbolic conservation laws, radiative transfer, and wave propagation Well-balanced schemes for geophysical and astrophysical flows High-order adaptive algorithms for phase field models and nonlinear PDEs Structure-preserving numerical methods for Hamiltonian systems and energy conservation Recent work emphasizes asymptotic preserving methods for multiscale problems, positivity-preserving techniques, and applications to relativistic radiation transport and shallow water equations. Articles often address stability, error analysis, and computational efficiency in complex physical systems. His contributions include pioneering work on DG methods for the Euler equations with gravitational fields and innovative treatments of discontinuous bottom topography in shallow water modeling. Despite extensive publications, no specific awards or grants are explicitly listed in the provided text.

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Cuneyt Sertمشاهده پروفایل

استاد

Middle East Technical UniversityTurkey

Prof. Cuneyt Sert is a faculty member in the Department of Mechanical Engineering at Middle East Technical University (METU), where he teaches courses such as Fluid Mechanics, Numerical Methods, and Computational Fluid Dynamics (CFD). His academic rank is Professor, reflecting his extensive contributions to research and education. He actively supervises graduate students, including PhD candidate Burcu Ramazanlı, whose work on abdominal aortic aneurysm hemodynamics led to a 2024 publication in the Journal of Thermal Science and Technology. Prof. Sert's research focuses on CFD, fluid dynamics, and biomedical applications. His studies on hemodynamics, turbulence, and material response in aerospace systems have produced influential papers since 2000. He is known for developing innovative numerical methods, such as adaptive discontinuous Galerkin techniques and CUDA-based parallel CFD solvers. His work bridges engineering education and industry, with projects on cryocooler optimization, metro aerodynamics, and grid fin aerodynamics. In teaching, Prof. Sert is praised for his student-centered approach, detailed lecture notes, and rigorous assignments. He emphasizes practical skills like MATLAB and C programming, though some students note concerns about workload and attendance policies. His courses, such as ME 310 (Numerical Methods) and ME 485 (CFD), are recognized for their rigor and real-world relevance. Prof. Sert’s contributions extend to interdisciplinary collaborations, including biomedical acoustics and material science. He has pioneered GPU-accelerated CFD tools and contributed to the design of microchannel heat exchangers. Despite no explicit awards listed, his peer reviews highlight his dedication to fostering critical thinking and problem-solving in students, earning him recognition as one of METU’s most respected educators.

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Per-Olof Perssonمشاهده پروفایل

استاد

University of California, BerkeleyUnited States

Per-Olof Persson is a Professor in the Department of Mathematics at the University of California, Berkeley . He is also a Senior Scientist at the Lawrence Berkeley National Laboratory , where he contributes to applied mathematics and computational physics research. Research Interests: Applied Mathematics Numerical Methods Computational Fluid and Solid Mechanics Discontinuous Galerkin Methods High-Order Discretizations Mesh Generation Recent Publications (2023-2025) demonstrate expertise in geometric multigrid, shock capturing, solution transfer between curved meshes, and optimization techniques. Key trends include advancements in high-order accuracy for fluid dynamics, implicit-explicit time-stepping, and interdisciplinary applications in aerospace and biomedical engineering. Advising: Supervised multiple PhD and Master’s students in topics spanning shock tracking, fluid-structure interaction, and computational solvers. Collaborates with institutions like MIT, KTH Royal Institute of Technology, and Lawrence Berkeley National Lab.

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Michael David Königمشاهده پروفایل

مدرس

ETH ZurichSwitzerland

Michael David König is a Lecturer at the Department of Management, Technology, and Economics at ETH Zürich, specializing in Innovation Economics within the KOF Swiss Economic Institute. His research focuses on the intersection of network theory and economics, particularly examining R&D networks, technology spillovers, and innovation dynamics. König maintains an active research profile with publications spanning economics, network science, and computer science. König's research spans multiple domains including economic network analysis, innovation economics, and technology diffusion. He has made significant contributions to understanding how firms form R&D collaborations and how knowledge flows through these networks. His work combines theoretical modeling with empirical analysis of large-scale network data, revealing patterns such as oscillatory dynamics in R&D collaboration intensity. Recent research has also addressed practical economic issues, including firm responses to the COVID-19 pandemic and factors influencing R&D investment decisions in Switzerland. His interdisciplinary approach bridges economics with computational methods, reflecting his background in both theoretical and applied network analysis. König's publication record demonstrates a strong interdisciplinary trajectory, beginning with contributions to wireless network protocols and distributed systems before focusing more intensively on economic applications of network theory. A consistent theme across his career has been the study of how networks evolve and how these structures influence outcomes in various domains, from technology diffusion to economic fluctuations. His research often employs sophisticated modeling techniques to analyze the coevolution of networks and economic behavior, with particular attention to the dynamics of knowledge creation and diffusion. König teaches Introduction to Microeconomics at ETH Zürich, as evidenced by his listing in the Autumn Semester 2025 course catalog. His office is located at LEE G 224, Leonhardstrasse 21, 8092 Zürich, Switzerland. He is affiliated with the KOF Innovation Economics research group, which focuses on innovation, technological change, and their economic implications.

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Fan Zhangمشاهده پروفایل

پژوهشگر ارشد

University of OsloNorway

Fan Zhang is a Postdoctoral Fellow at the Rosseland Center for Solar Physics, University of Oslo, specializing in computational fluid dynamics and solar plasma modeling. His research bridges high-order numerical methods with astrophysical applications, particularly in magnetohydrodynamics (MHD) for solar corona and wave propagation studies. University of Oslo Rosseland Center for Solar Physics Research Interests Zhang's work focuses on advancing numerical techniques for shock-capturing and MHD simulations, enabling precise modeling of solar phenomena like coronal mass ejections (CMEs), Alfvén waves, and plasma dynamics. He develops finite-volume and compact nonlinear schemes tailored for unstructured grids, addressing challenges in numerical stability and accuracy. Recent Publications His 15 most recent articles (2025–2021) highlight innovations in time-accurate MHD models (e.g., SIP-IFVM, COCONUT), mesh topology effects on solar simulations, and algorithms for overshooting oscillation suppression. Key themes include computational efficiency, high-order numerical schemes, and two-fluid modeling of solar plasmas. Collaborative Work Zhang frequently collaborates with international researchers on projects like COCONUT, which optimizes preprocessing of magnetic maps for space-weather forecasting and solar cycle modeling. His contributions span algorithm design, model validation, and cross-disciplinary computational frameworks.

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