Find Academic Supervisors

• Physical Oceanography
• Marine Turbulence and Current Dynamics
• Tidal Energy and Renewable Resources
• +3 more

Professor Göran Broström works at the Department of Marine Sciences at the University of Gothenburg . His research focuses on physical oceanography, marine turbulence, tidal energy systems, and biophysical processes in marine ecosystems. Current research themes include methane emissions from ocean infrastructure, turbulence in tidal flows, and wave-current interactions He utilizes advanced numerical modeling (e.g., Large Eddy Simulation, Bayesian inversion) and field observations Recent publications emphasize climate impacts (methane plumes), tidal energy innovations, and marine ecological connectivity His work appears in high-impact journals like Nature , Molecular Ecology , and Frontiers in Marine Science . Collaborative projects span oceanographic modeling, environmental monitoring, and marine renewable energy. No specific student advising information appears in the provided text.

• Mathematical Physics
• Integrable Systems
• Superconductivity Theory
• +3 more

Edwin Langmann is a Professor of Physics at KTH Royal Institute of Technology in Stockholm, Sweden. He holds a PhD in Theoretical Physics from the University of Vienna (1990) and has held academic positions including Assistant Professor at KTH (1994–1998), Postdoc at the University of British Columbia (1991–1994), and various roles at Swedish institutions since 2000. His research focuses on mathematical physics, integrable systems, and superconductivity theory, with contributions to quantum many-body systems and exactly solvable models. Affiliations: Department of Condensed Matter Theory, KTH Royal Institute of Technology Educations: PhD (Theoretical Physics, University of Vienna, 1990), M.Sc. (Technical Physics, TU Graz, 1986) Langmann teaches courses in physics and mathematical methods, advising numerous master’s theses. His work bridges theoretical physics and mathematics, addressing topics like Calogero-Sutherland models, fractional quantum Hall effects, and Hubbard model phase diagrams. Recent research includes antiferromagnetic order in 3D systems and BCS superconductivity with finite-range potentials. He has supervised students including Frode Boman (2021), Max Oliveberg (2021), and Charles Gilljam (2020). His publications span journals such as Communications in Mathematical Physics and Physical Review B , emphasizing integrable systems and quantum field theory.

Lina von SydowView profile

Professor

• Computational Science
• Computational Finance
• Ice Sheet Modeling
• +2 more

Lina von Sydow is a Professor in Computational Science at Uppsala University's Department of Information Technology. She serves as Section Dean for the Mathematical-Computer Science Section since July 2023. Her academic journey includes becoming an Associate Professor in 2000, Senior Lecturer since 1997, and leading the Department of Information Technology from 2018 to 2023. PhD in Domain Decomposition Methods (1995, Uppsala University) Postdoctoral Fellow at Oxford University (1996-1997) Her research spans computational science with dual focuses on Computational Finance and Ice Sheet Modeling . In finance, she develops numerical methods for option pricing using PDEs, radial basis functions, and stochastic volatility models. In climate science, she contributes to ice sheet dynamics through full Stokes models and adaptive time-stepping approaches, particularly in simulating grounding line migration. Recent publications (2025) address gender disparities in IT education, including comparative analysis of admission trends and intervention studies to boost female enrollment. Earlier works (2020-2015) focus on high-order finite difference methods for financial derivatives, BENCHOP benchmarking projects, and preconditioning techniques for PDEs. Scientific awards include Excellent Teacher (2013) She actively collaborates on educational reforms, co-authoring studies like Gender-aware course reform in Scientific Computing (2013). Her leadership roles include Head of Department (2018-2023) and Section Dean (2023-present), influencing academic governance and interdisciplinary research. Labs and teams: Works with Uppsala University's Computational Science group, Elmer/ICE project collaborators (e.g., Per Lötstedt, Gong Cheng), and international partners in numerical finance and climate modeling.

• Numerical Analysis
• Differential Equations
• Geometric Numerical Integrators
• +3 more

David Cohen is a Professor in the Department of Applied Mathematics and Statistics at Chalmers University of Technology. His academic career centers on the development and analysis of numerical methods for differential equations, with particular expertise in geometric numerical integration techniques. His research focuses on structure-preserving numerical methods for approximating solutions to deterministic and stochastic dynamical systems. Cohen's work spans geometric numerical integrators, stochastic differential equations, and the numerical analysis of partial differential equations. His approach emphasizes preserving underlying geometric structures in numerical schemes, which is crucial for long-term accuracy and stability in simulations. The publication record shows consistent research output with a clear trajectory toward increasingly complex stochastic systems. Recent work focuses on splitting integrators, positivity-preserving schemes, and specialized methods for stochastic wave equations, Manakov systems, and Lie-Poisson structures. His research demonstrates strong connections to applications in physics, optics, and mathematical modeling of complex systems. Cohen leads or participates in multiple research projects funded by Vetenskapsrådet (VR) and the European Commission, including work on stochastic FitzHugh-Nagumo models and numerical methods for PDEs with random dispersion. His collaborative network includes researchers across Europe and North America, reflecting the international nature of his work in computational mathematics.

• Computational Fluid Dynamics
• Numerical Methods
• Multiphase Flow
• +3 more

Katarina Gustavsson is an Associate Professor at KTH Royal Institute of Technology, affiliated with the Department of Numerical Analysis, Optimization and Systems. She serves as the Head of Studies (Huvudstudierektor) for the Department of Mathematics and teaches courses such as the Basic Course in Numerical Methods (SF1525) and Numerical Methods, Basic Course (SF1547). Her research focuses on computational fluid dynamics, multiphase flow, and boundary treatment techniques in numerical simulations. Her work includes developing numerical methods for rigid fiber suspensions, sedimentation analysis, and contact line dynamics. Key contributions involve high-accuracy boundary treatments for Stokes flow and conservative level set methods for interface dynamics. She has authored over 20 peer-reviewed articles and conference papers since 2000. Dr. Gustavsson’s research interests span fluid-structure interaction, fiber orientation dynamics, and the numerical modeling of complex multiphase systems. Her publications address challenges in Stokes flow simulations, sedimentation processes, and the consolidation of concentrated suspensions.

• Contrastive syntax
• Corpus-based translation analysis
• Generative linguistics
• +7 more

Jenny Ström Herold is a Senior Lecturer at Linnaeus University , Faculty of Arts and Humanities, Department of Languages. She coordinates the Non-fiction Translation Master Programme (German and English specializations) and serves as contact person for the Center for Technical Language (CFS) . Her work includes both teaching and research within contrastive syntax and corpus-based translation analysis. Linguistic research: Generative linguistics Translation studies: Phraseological phenomena Corpus analysis: English-German-Swedish comparisons Project member of Swedish Research Council-funded research (2023-2026) Her publications since 2006 focus on: Light verb constructions (e.g., "take a look"/"in Auftrag geben") Complex premodifiers ("do-it-yourself books") Punctuation strategies (dashes, colons, brackets) Anaphoric reference mechanisms Acronym translation patterns (BBC/PFC/CAPTCHA) Proper noun modifier translation

• Theoretical Computer Science
• Artificial Intelligence
• Parameterized Complexity
• +3 more

George Osipov is a researcher at Linköping University's Department of Computer and Information Science (IDA), affiliated with the Faculty of Science and Engineering. He holds a PhD in Computer Science from Linköping University, where his thesis focused on the parameterized complexity of constraint satisfaction problems (CSPs) at the intersection of theoretical computer science and artificial intelligence. His work explores efficient algorithms for solving almost-satisfiable CSPs, emphasizing scalability and practical applications in data processing and automatic reasoning. Education: Bachelor's in Computer Science from Free University of Tbilisi, Georgia; Master's in Mathematics from Ilia State University, Georgia (with an Erasmus year in Uppsala University, Sweden). Affiliations: Member of the Wallenberg AI, Autonomous Systems and Software Program (WASP) graduate school; Postdoctoral researcher funded by the Swedish Research Council. Collaborations: Partnered with institutions in the UK (Royal Holloway, Newcastle, Leeds), Germany (Saarbrücken), and Poland (Warsaw). His research interests include parameterized complexity, constraint satisfaction problems, and algorithm design, with a focus on theoretical foundations and practical applications. He has received the prestigious 2023 Lawson Scholarship for excellence in computer science and is currently conducting postdoctoral research at Oxford University and Royal Holloway University of London. His work bridges theoretical computer science and AI, addressing challenges in scalable algorithmic solutions for complex computational problems. George's contributions have been recognized through grants and international collaborations, reflecting his commitment to advancing the frontiers of computational theory and its real-world utility.

Flavius GruianView profile

Senior Lecturer

• Embedded Systems
• Real-Time Systems
• Hardware-Software Co-Design
• +5 more

Flavius Gruian is a Senior Lecturer and Reader Project Manager at the Department of Computer Science, Lund University (LTH). He holds affiliations with ELLIIT (Linköping-Lund initiative on IT and mobile communication) and the LTH Profile Area: AI and Digitalization. His research focuses on resource-constrained embedded systems, real-time scheduling, and energy-efficient hardware-software co-design, with applications in IoT, radar systems, and radio astronomy. Education and Academic Roles: No explicit education details provided, but his roles include senior lecturer, project manager, and principal investigator (PI) in multiple research projects. He advises PhD students (Boulasikis, Callanan, Waldemarson) and contributes to initiatives like GPAI (AI hardware for computing) and NordicIoT (Nordic IoT hub). Research Interests: His work spans embedded systems modeling, real-time algorithms, custom hardware architectures, Java in embedded systems, and machine learning for industrial applications. He explores energy-efficient designs and reliability in distributed embedded systems. Key Projects: Active projects include GPAI (2021–2026), TaLMiRRA (machine learning in radar/astronomy, 2019–2022), and NordicIoT (2018–2023). He also leads research on scalable actor networks and GPU programming for visual systems. Grants and Funding: PI roles in TaLMiRRA (STINT-funded) and NordicIoT (Nordic collaboration). Projects involve collaboration with international teams and industry partners. Labs/Teams: Affiliated with ELLIIT and the LTH AI profile area. Collaborates on hardware-software co-design and embedded systems optimization.

Pan LuView profile

Research Fellow

• Computational Electromagnetics
• Topology Optimization
• Microwave Imaging
• +3 more

Pan Lu is a Postdoctoral Fellow in the Design Optimization Group at the Department of Computing Science, Umeå University. His research focuses on computational electromagnetics, topology optimization, and microwave imaging using finite difference time domain methods. Contact: Email: pan.lu@umu.se ORCID: 0000-0002-9128-4728 Current research addresses topology optimization of electromagnetic wave-related problems, including dualband metallic antenna design with minimum-size control. Affiliation: Department of Computing Science, Umeå University Design Optimization Group

• Numerical Analysis
• High Performance Parallel Computing
• Algorithm Design
• +5 more

Carl C Kjelgaard Mikkelsen is an Associate Professor at the Department of Computing Science, Umeå University, Sweden. His research focuses on developing robust numerical algorithms that cannot fail, particularly in the context of finite precision arithmetic used by computers. His work bridges theoretical numerical analysis with practical high-performance computing applications. Dr. Mikkelsen's research interests center around numerical analysis and high performance parallel computing, with special emphasis on the worst case analysis of algorithms. He investigates the profound differences between exact arithmetic used by humans and finite precision arithmetic used by computers. His current projects include developing parallel constraint solvers for constrained molecular dynamics and parallel solvers for ultra-sparse linear systems. He is a co-author of the StarNEig library for solving dense nonsymmetric standard and generalized eigenvalue problems in parallel. His recent publications demonstrate a strong focus on accuracy requirements in numerical methods, particularly Newton's method, and the development of robust parallel algorithms for linear algebra problems. His work spans from theoretical analysis of numerical stability to practical implementation in high-performance computing environments. Dr. Mikkelsen teaches numerical analysis and scientific computing, emphasizing algorithm design, analysis, and implementation. He focuses on teaching students the critical differences between exact and finite precision arithmetic, and invests significant time in teaching software development practices and technical writing.

• Applied Mathematics
• Materials Science
• Computational Modeling
• +3 more

Jens Wittsten is a Researcher affiliated with the Department of Engineering at the University of Borås' Academy of Textiles, Technology and Economics. He serves as the main supervisor for doctoral student Markus Klintborg and holds office in room C801. His work bridges applied mathematics, materials science, and computational engineering. Research interests include modeling phenomena in moiré heterostructures (e.g., twisted graphene layers), semiclassical quantization in strained lattices, and seismic data processing techniques. He has contributed to understanding electronic phase transitions, magic angles in bilayer graphene systems, and numerical methods for wave propagation modeling. His publication trends reflect interdisciplinary focus: recent works address both fundamental physics (e.g., Hofstadter butterfly studies) and applied engineering challenges (e.g., warehouse optimization via GPU-accelerated routing). Jens advises one doctoral candidate and maintains an active research portfolio spanning over 25 peer-reviewed articles since 2010. His methodological innovations include contributions to seismic apparition techniques and dealiasing algorithms.

Robert-Zoltán SzászView profile

Researcher

• Fluid Mechanics
• Computational Fluid Dynamics
• Large Eddy Simulation
• +4 more

Robert-Zoltán Szász is a Researcher in the Department of Energy Sciences at Lund University, Faculty of Engineering, and a member of the LTH Profile Area: The Energy Transition. His work centers on numerical modeling of fluid flows. His research interests encompass: Numerical modeling of swirling reacting and non-reacting flows Computational aeroacoustics Wind turbine aerodynamics Ice accretion phenomena He employs Large Eddy Simulations and Computational Fluid Dynamics to address energy system challenges, with recent focus on hydrogen-enriched combustion dynamics and ice accretion modeling for renewable infrastructure. Szász has supervised 6 students and contributed to key projects: Numerical and experimental investigation of a gas turbine model combustor : Dissertation project examining swirling flows in combustion systems Computations of ice throw/fall : 2018-2019 research on ice formation/detachment modeling

• Numerical Analysis
• Scientific Computing
• Finite Difference Methods
• +4 more

Sofia Eriksson is an Associate Professor in the Department of Mathematics within the Faculty of Technology at Linnaeus University. She specializes in numerical analysis and scientific computing, with a primary focus on developing finite difference methods for solving time-dependent partial differential equations. Her research has significant applications in fluid dynamics and aerodynamics. Dr. Eriksson's research interests span numerical analysis, scientific computing, finite difference methods, partial differential equations, and computational mathematics. She leads or participates in two major research groups: Computational Mathematics for Predictive Digital Twins (PreDiTwin) and Scientific Computing and Partial Differential Equations. Her work emphasizes developing stable numerical methods with proper boundary and interface treatments. Her publication record shows consistent output since 2007, with 15 recent publications spanning journals like Journal of Computational Physics, SIAM Journal on Numerical Analysis, and Foundations of Computational Mathematics. Her research shows a clear progression from foundational work on finite difference methods to more specialized applications in fluid dynamics and aerodynamics. The publications demonstrate expertise in developing stable numerical schemes, particularly for time-dependent problems with complex boundary conditions. Dr. Eriksson teaches courses in Numerical Methods, Linear Algebra, and Calculus, contributing to both undergraduate and graduate education in mathematics and computational science. Her teaching reflects her research expertise, providing students with practical knowledge of numerical methods applicable to real-world scientific and engineering problems.