CV
Experience
Day-ahead nodal price forecasts and automated bidding for battery storage and solar assets in CAISO and MISO.
Day-ahead, real-time and long-term power price forecast models across US ISOs; scenario and optimization models for energy storage dispatch and asset valuation.
Machine learning models for power market revenue forecasting; day-ahead vs. real-time price spread (DART) forecasts for ERCOT settlement points.
Bayesian spatiotemporal models linking brown and white shrimp distributions on the Louisiana shelf to hypoxia and other environmental factors.
Bayesian mechanistic and statistical models forecasting hypoxia and algal blooms in the Neuse River Estuary and the northern Gulf of Mexico.
Industrial hydraulics market analysis, trade show and conference management, corporate website.
Education
Dissertation: Bayesian modeling of coastal eutrophication to inform management solutions for hypoxia and algal blooms. Advisor: Daniel R. Obenour.
Thesis on submarine groundwater discharge in a granitic coastal area of Japan, using radon-222 as a natural tracer.
Skills
Time series and probabilistic forecasting, Bayesian and stochastic modeling, gradient boosting, quantile regression and conformal calibration, linear and mixed-integer optimization. R (tidyverse, data.table, Stan), Python (pandas, NumPy, scikit-learn, Pyomo), SQL, AWS, GCP, Docker, Git.
Publications
Four first-author papers, listed on the PhD research page and on Google Scholar.