Dan Lu

Bio

Dan Lu is a senior staff scientist in the Computational Earth Sciences Group at Oak Ridge National Laboratory. 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, Inverse Modeling, Sensitivity Analysis, Experimental Design, and Numerical Simulations in Earth, Climate and Environment Sciences. Dan is the PI of a UQ for ML project, the PI of a Hydropower project, and the PI of a Geological Carbon Storage project. Dan authored about 70 publications and co-developed two softwares. 

Her personal webpage is here.

Awards

DOE Early Career Award.

Professional Service

1. Topical Editor: Geoscientific Model Development, 2021 -- Present

2. Associate Editor: Artificial Intelligence for the Earth Systems, 2021 -- Present

3. Associate Editor: Frontiers in Water, 2022 -- Present

4. Editor: Special issue on Data-driven machine learning for advancing hydrological and hydraulic predictability, Frontiers in Water, 2022.

5. Co-editor: Special issue on advances in multiphase flow and transport in the subsurface environment, Geouids, 2018.

6. Groundwater Technique Committee for American Geophysics Union, 2016 -- Now.

7. Program Committee for Tackling Climate Change with Machine Learning Workshop at NeurIPS Conference, 2022 -- Present.

8. Program Committee for AI for Robust Engineering and Sciences Workshop, 2021-2022.

9. Program Committee for Climate and Weather Domain of PASC19 Conference, 2019.

10. Review Committee for Enzyme Engineering Initiative at ORNL, 2022-2023.