Collegium Helveticum
Switzerland
fellow
Tülin Kaman
2024-2025
Home institution
University of Arkansas
Country of origin (home institution)
United States
Discipline(s)
Computers and intelligent systems; Mathematics
Theme(s)
Digital Society; Environment, Sustainability & Biodiversity
Fellowship dates
›
Biography
Tülin Kaman is an associate professor and the Lawrence Jesser Toll Jr. Chair in the Department of Mathematical Sciences at the University of Arkansas (US). Her research focuses on the modeling and simulations in fluids, numerical methods for partial differential equations, computer aspects of numerical algorithms in scientific parallel computing, and uncertainty quantification.
She leads the Computational and Applied Mathematics research group, which studies the verification, validation, and uncertainty quantification of turbulent mixing and combustion in engineering applications. Tülin received her PhD in Applied Mathematics and Statistics from Stony Brook University in New York (US), winning the Woo Jong Kim Dissertation Award. She was a Paul Scherrer Institute Fellow (CH), a post-doctoral researcher and lecturer in the Department of Computer Science at ETH Zurich (CH) and the Institute of Mathematics at the University of Zurich (CH). She serves as the faculty advisor of the University of Arkansas Association for Women in Mathematics (AWM) and Society for Industrial and Applied Mathematics (SIAM) Student Chapters, is the chair of the SIAM Membership Committee, and is a member of the AWM Membership & Community Portfolio Committee.
Research Project
Uncertainties in Extreme Weather Predictions
Understanding the dynamics of unpredictable systems like weather forecasting has been one of the most important as well as challenging problems in the environment, economy and society. From an environmental perspective, the rising global temperatures, melting glaciers, increasing sea levels, and more severe weather events disturb the ecosystems and influence biodiversity. From an economic perspective, severe weather events such as hurricanes, heatwaves, and floods affect agriculture, infrastructure and energy consumption. The verification, validation and uncertainty quantification (VVUQ) studies are crucial for achieving reliable and accurate results through high-fidelity multi-physics and multiscale modeling and simulations.
This project focuses on the VVUQ of weather and climate modeling and simulations on high-performance computing systems with an emphasis on visualizing extreme weather predictions. The primary goal of this project is to understand and develop accurate and efficient models for extreme weather simulations.
Research Interests:
climate modelling; weather forecasting; uncertainty quantification; verification and validation; high-performance computing; multiscale modelling; multi-physics simulation; extreme weather events.