جست‌وجوی استاد و پژوهشگر

• Numerical Analysis
• Stochastic Differential Equations
• Runge-Kutta Methods
• +۴ مورد دیگر

Anne Kværnø is a Professor in the Department of Mathematical Sciences at NTNU. Her research focuses on numerical analysis, particularly stochastic differential equations, Runge-Kutta methods, and geometric integration. She has made significant contributions to the development of high-order numerical schemes for stochastic systems, including exponential integrators and Lawson schemes. Her work emphasizes preserving invariants and stability properties in stochastic and deterministic systems. Key research areas include multirate methods for coupled systems, differential-algebraic equations, and applications in energy storage modeling. She has collaborated extensively on projects involving aquifer thermal energy storage (ATES) systems and groundwater flow analysis. Her publications span prestigious journals like BIT Numerical Mathematics, SIAM Journal on Numerical Analysis, and Journal of Computational Physics. She has presented at major conferences such as ICIAM, SciCADE, and ENUMATH, focusing on stochastic numerical methods and their applications. Her research bridges theoretical developments with practical computational challenges in engineering and environmental modeling.

Torstein Kastberg Nilssenمشاهده پروفایل

دانشیار

• Nonlinear stochastic partial differential equations
• Rough paths
• Malliavin calculus
• +۲ مورد دیگر

Torstein Kastberg Nilssen is an Associate Professor in the Department of Mathematical Sciences at the University of Agder, Norway (since 2019). He has held postdoctoral positions at Technische Universität Berlin (2017-2019), University of Oslo (2014-2017), and guest researcher roles at University of Southern California (2015-2016), University of Manchester (2014), and Humboldt University Berlin (2013). Current affiliation: University of Agder Prior institutions: TU Berlin, University of Oslo, USC, University of Manchester, Humboldt University Berlin Research Focus: Nilssen's work revolves around nonlinear stochastic partial differential equations, rough path analysis, Malliavin calculus, and regularization effects of noise in systems with irregular coefficients. His research explores pathwise solutions for rough PDEs, stochastic transport equations, and robust methods in fluid dynamics under rough perturbations. Publication Trends: Recent articles (2019-2025) emphasize rough path applications to fluid mechanics, geometric rough paths in infinite dimensions, McKean-Vlasov dynamics for Kalman filters, and regularization of SDEs/PDEs with singular drift. Key keywords include stochastic differential equations, fractional Brownian motion, variational principles, and nonlocal diffusions.

• Numerical Analysis
• Machine Learning
• Computational Mathematics
• +۴ مورد دیگر

Jonas Kusch is an Associate Professor at the Department of Data Science, Norwegian University of Life Sciences, specializing in numerical analysis and its applications in scientific computing and machine learning. His work focuses on dynamical low-rank approximation, particularly in developing low-rank neural networks with geometry-aware training algorithms that respect the differential geometry of matrix manifolds. Research spans computational quantum mechanics , radiation transport , and machine learning . Key contributions include energy-stable integrators for kinetic equations and multi-fidelity optimization algorithms for fission criticality. Publications emphasize low-rank methods for solving inverse problems, time-dependent systems, and uncertainty quantification in hyperbolic equations.

Jochen Jungeilgesمشاهده پروفایل

استاد

• Economic Dynamics
• Applied Econometrics
• Nonlinear Deterministic and Stochastic Dynamic Systems
• +۳ مورد دیگر

Jochen A. Jungeilges is a Professor of Economics at the Department of Economics and Finance, School of Business and Law, University of Agder. He holds academic qualifications including Master's degrees in Economics (University of Bielefeld) and Applied Statistics (Louisiana State University), a PhD in Economics (University of Bielefeld), and a Habilitation from the University of Osnabrück. His research focuses on economic dynamics and applied econometrics, with particular emphasis on nonlinear deterministic and stochastic dynamic systems in micro- and macroeconomics, statistical methodology, and empirical social choice. Recent work explores network analysis applications to financial time series. Publications appear in journals like the Journal of the European Economic Association, Communications in Non-linear Science & Numerical Simulation, and Structural Change and Economic Dynamics. Teaching responsibilities include Financial Econometrics (SE-419), Empirical Finance (SE-510), and Machine Learning with Applications in Finance (SE-507). He has served on appointment boards, participated in international dissertation procedures, and reviewed for journals like the Journal of Economic Behavior & Organization.