Posts classified under: Advising Faculty

My research interests include analysis of high throughput biological data, for instance finding age-related genes in multiple species and tissues with the Kim lab. I am generally interested in settings where both rows and columns of the data matrix correspond to entities of interest, that is, neither are IID. Special interests include adjusting for the effects of latent variables, finding ways to bootstrap and cross-validate non-IID data, and making extensions to three-way and higher order data arrays. I also work on Monte Carlo methods.

Research focuses on CT and other medical imaging modalities. Our lab is currently interested in efficient and reproducible methods of extracting and visualizing medical information from the thousands of images typically generated by one or more radiological exams performed for each patient.

Experimental and theoretical systems neuroscience: Cognitive neuroscience; Cognitive development; Psychiatric neuroscience; Functional brain imaging; Dynamical basis of brain function; Nonlinear dynamics of neural systems.

Maya Mathur is an interdisciplinary statistician whose research develops methods for sensitivity analysis and for evidence synthesis, particularly meta-analysis. Current focuses include developing methods for the analysis of multisite replication studies, methods for assessing and correcting for publication bias, and methods for synthesizing replication studies with existing literature. Her substantive research focuses on behavior and health and the experimental cognitive sciences; for example, her most recent empirical direction focuses on behavioral interventions to reduce meat consumption.