About Me
I am an applied mathematician, currently working in the position of Senior Research Scientist in Environmental Sciences and Engineering at the California Institute of Technology.
I work primarily in the Climate Modeling Alliance (CliMA) under Prof. Tapio Schneider and Prof. Andrew Stuart, using Bayesian uncertainty quantification, data assimilation, and machine learning techniques to improve climate model prediction.
Research interests
My current interests are in mathematical and statistical modeling for physical systems, and in the corresponding inverse and data assimilation problems to learn from data.
I have experience with mathematical methods such as optimization and variational methods for partial differential equations, modeling free boundary and shape optimization problems, regularization for deterministic inverse problems, and fluid and solid mechanics. I also have experience in statistical methods such as Bayesian inverse problems, uncertainty quantification, data assimilation, Bayesian experimental design. Most recently I have been working on machine learning (Gaussian Processes, Random Features, Reservoir Computers) and model emulation, graph-based learning, and partial differential equations on graphs.
Contact
Work details
Latest News!
(June 10th – 12th, 2024) Invited speaker to SIAM MPE24, MS: “Accelerating Uncertainty Quantification for Models of Climate and Weather”, June 2024, Portland, OR, USA
(April 15th – 16th, 2024) Invited participant to CaCAO Days, April 2024, University of California San Diego, CA, USA
(February 27th – March 1st, 2024) Invited speaker to SIAM UQ24, MS75: “Bayesian Inverse Problems Governed by Partial Differential Equations”, February 2024, Trieste, Italy
(September 26th – 27th, 2023) NSF PI meeting, Houston, Overview of some successes from the CliMA project in the field of systematic calibration with the poster, “Data-driven ocean, atmosphere, and land parameterizations calibrated from indirect data”
(August 20th – 25th, 2023) ICIAM 2023 Tokyo, I am a co-organizer and presenter in the Minisymposium 00831:Randomization for Simplified Machine Learning: Random Features and Reservoir Computers, Jointly organized with Georg Gottwald, Matthew Levine, and Nicholas Nelsen
(June 19th – 23rd, 2023) Invited speaker to SIAM GS23, MS33: Advances in Bayesian Inversion for Geoscience Problems.
Dr. Oliver R. A. Dunbar 