Posts classified under: DBDS

Hybridization between species is a common process in the evolutionary history of many species, including our own. Despite this, the evolutionary consequences of hybridization are still relatively poorly understood. We focus on using genomic, computational and experimental approaches to understand how hybridization shapes the evolution of genomes and species. Current projects in the lab include developing new approaches to detect selection after hybridization, time-transect monitoring of hybrid genome evolution, and understanding the genetic architecture of hybrid incompatibilities.

https://schumerlab.com/

We are a computational neuropsychiatry lab, dedicated to developing methods for a better understanding of individual differences in brain functioning in healthy and psychiatric populations. We primarily work with noninvasive human neuroimaging data (fMRI, EEG, and fNIRS). We are currently working in these three areas – [a] Modeling spatiotemporal dynamics in brain activity to develop person- and disorder-centric biomarkers; [b] Understanding the role of brain dynamics for optimized learning and performance (e.g., creativity) in individual and team settings; and [c] Developing methods that use network science, machine learning, and signal processing for better understanding of brain dynamics.

Sherri Rose, Ph.D. is an Associate Professor of Health Policy and Co-Director of the Health Policy Data Science Lab at Stanford University. Her research is centered on developing and integrating innovative statistical machine learning approaches to improve human health and health equity. Within health policy, Dr. Rose works on risk adjustment, ethical algorithms in health care, comparative effectiveness research, and health program evaluation. She has published interdisciplinary projects across varied outlets, including Biometrics, Journal of the American Statistical Association, Journal of Health Economics, Health Affairs, and New England Journal of Medicine. In 2011, Dr. Rose coauthored the first book on machine learning for causal inference, with a sequel text released in 2018. She has been Co-Editor-in-Chief of the journal Biostatistics since 2019. Read more about the Health Policy Data Lab.