Two new NSF Awards to SDS Faculty this year

The National Science Foundation awarded grants to two Statistics and Data Science faculty members, Professors Nan Lin and José Figueroa-López this year.

Nan Lin has received a new NSF award for his project titled “Quantile Regression in the Big Data Regime: Online Learning, Missingness, and Causality.” Quantile regression is a powerful statistical tool that goes beyond the “average” relationship captured by traditional regression analysis. This project will address the challenges of big data in quantile regression by developing methods that achieve computational efficiency without sacrificing statistical accuracy. These new methods are needed in various fields, including economics, finance, social sciences, and healthcare.

José Figueroa-López has been awarded a new NSF grant for his project “Collaborative Research: Systemic Shock Inference for High-Frequency Data.” Unexpected shocks during periods of stability naturally occur in time-dependent data-generating mechanisms across various disciplines. High-frequency observations of such systems appear in econometrics, climatology, statistical physics, and many other empirical sciences that can benefit from reliable inference of shock events. This project aims to develop new statistical techniques for detecting and analyzing shocks in large systems of time-dependent variables observed at high temporal sampling frequencies.

Both projects will play active roles in student training at SDS.

Congratulations to Nan and José!