Marcela Alfaro

University of California, Santa Cruz

Assistant Teaching Professor at the University of California, Santa Cruz. She is interested in developing novel statistical methods to address scientific questions related to the environment, and turning those experiences of interdisciplinary collaboration into teaching methods for statistics and data science. Her areas of application include climate models, biophysics, spectrophotometry, among others.

https://malfaro.netlify.app/

Marcos Matabuena

Harvard University

Marcos Matabuena, a Spanish mathematician at Harvard University, specializes in mathematical models for digital medicine. He focuses on uncertainty quantification, survival analysis, and causal inference, crucial for predicting clinical events and optimizing treatments. In diabetes research, his models interpret continuous glucose monitor data. He also studies aging-related decline using wearable device data. Marcos developed the first uncertainty quantification framework for regression models in metric spaces and introduced 'glucodensity,' a functional representation for interpreting continuous glucose monitoring and wearable device data. He also created the first biclustering algorithm in RKHS spaces for complex data analysis.