Dacian Daescu

Prof. Daescu research interests are in applied and computational mathematics and data-enabled science to analyze and predict the state of complex dynamical systems that are mathematically modeled by nonlinear ordinary differential equations (ODEs) or partial differential equations (PDEs) systems. His application-oriented research on data assimilation, model-constrained optimization, sensitivity analysis, and uncertainty quantification relies on state-of-the-art numerical optimization algorithms, high-performance computing, inverse problems theory and statistical data analysis tools to improve the models' predictive capabilities and to develop new methodologies for observing system assessment, experimental design, and accurate representation of the uncertainty in model forecasts. Specific applications include geophysical and environmental problems of major societal impact such as numerical weather prediction and air pollution forecasting. Prof. Daescu’s research at PSU has been supported by grants and awards from NASA, NRL, NSF, and Intel Inc.