Amy Wagler

Biography

Dr. Amy Wagler is the Director of Research Computing and Data Science at New Mexico State University (NMSU). At NMSU, she coordinates and leads efforts around high performance computing (HPC) and data-intensive interdisciplinary research. These activities are coordinated through her role at NMSU to collaborate with the 33 NMSU Extension Offices located throughout the state and Los Alamos and Sandia National Laboratories. She also works to broaden access to HPC facilities to predominantly undergraduate institutions (PUIs) in the State of New Mexico. She coordinates a team of interns at the NMSU HPC and is involved in developing materials for workforce training in HPC. In her previous academic appointment at The University of Texas at El Paso, she developed Masters and Doctoral level degree programs in data science and was a leader in broadening access to data science training regionally and nationally, through her roles as Associate Chair of Mathematical Sciences and Director of Data Science. She is a 2014 winner of the UT System Regent’s Outstanding Teaching Award and received the C-USA Faculty Achievement Award in 2024.

Her methodological research interests include multiplicity corrections in high-dimensional settings and simultaneous inference in generalized linear model settings. This has application in any high-throughput data setting focused on test outcomes with complex dependency structures. She is also active in research on graph theory modeling, with a focus on comparison of complex networks and error control in these model settings. With Pacific Northwest National Labs colleagues, she investigated the use of differential privacy models for generating synthetic data in biomedical studies. Additionally, she engages in many applied community-based projects in the data sciences, in areas such as biology, biomedicine, and education. She has also made contributions on communication in statistics and data science in varied cultural and linguistic contexts and the integration of statistics and science content in teaching and public communication.