Lead Consultant at the Graduate Quantitative Methods Center, UC Riverside — workshops and one-on-one methods consulting for graduate students across the university.
GradQuant is UC Riverside’s campus-wide center for quantitative and computational methods training. As Lead Consultant I work with graduate students from every school on campus — on their own data, at whatever stage they have reached.
How the models work — tokens, embeddings, attention, Transformer blocks — then how to use them in research: when an LLM beats a dictionary, prompting reproducibly, and validating output against hand-coded samples. Demonstrated by scoring FOMC statements for hawkishness.
Four strategies for forecasting with many correlated predictors — PCA and factor models, partial least squares, Lasso, and neural networks — compared head to head on a simulated macro dataset and scored out of sample against an AR(1) benchmark.
Why time series breaks the OLS assumptions, and what to do about it: stationarity and unit roots, seasonal decomposition, reading ACF and PACF, then fitting and forecasting with ARIMA and SARIMA. Worked on U.S. real GDP and airline passengers.
The essentials from scratch in Colab — data types, lists and dictionaries, functions and modules, plotting with matplotlib — closing with a mini project that builds a Phillips curve from live FRED data.
Thirty-six scheduled appointments and twelve drop-ins, drawn from every school on campus — entomology, psychology, political science, computer science, materials science, public policy, economics and more. Twenty-one doctoral students, nine master’s, five postdocs; fifteen international.