Staff Scientist
Oak Ridge National Laboratory
Dan Lu is a research staff in the Computational Earth Science Group in the Computational Sciences and Engineering Division at Oak Ridge National Laboratory (ORNL). She earned her Ph.D. in Computational Hydrology at Florida State University in 2012 and joined ORNL in 2013 after one-year Postdoc in U.S. Geological Survey. Dan has broad research interests including: Machine Learning (ML), Uncertainty Quantification (UQ), Surrogate Modeling, Numerical Simulation in Earth, Climate and Environment Sciences, Inverse Modeling, Sensitivity Analysis, and Experimental Design. Dan is leading a UQ for ML project in the AI Initiative of ORNL and a physics-informed ML project funded by Fossil Energy Program. She is an Associate Editor of Artificial Intelligence for the Earth Systems, an Associate editor of Frontiers in Water, and a Topical Editor of Geoscientific model development.
An Uncertainty-Aware, Machine Learning-Enabled Reservoir Inflow Forecast Model
Wednesday, May 24, 2023
3:00 PM – 3:15 PM PDT