Our Team

Carl Stahmer is a digital humanist, leveraging his expertise as a computer programmer and system architect to tackle complex problems in the humanities and beyond. He received his PhD in English from UC Santa Barbara. He is a professor in English and Science and Technology Studies at UC Davis, and teaching faculty at the Rare Book School. His interests include natural language processing, computer vision, and library science.

Pamela Reynolds has a background in interdisciplinary research and team science. She manages DataLab’s research projects and training programs. She teaches computational tools and thinking to enable innovation and student success. Pamela received her PhD in Biology from UNC Chapel Hill, and bachelor’s in Biological Sciences and English from UC Davis. She led a global research network for her postdoc. Her interests include experimental design, statistical modeling, and data science pedagogy.

Michele Tobias is a geospatial data scientist with a background in geospatial methods for ecology. Michele earned her PhD from UC Davis in Geography where she studied California’s sandy beach ecosystem with traditional phytosociological methods and innovative remote sensing tools and was a postdoc at the UC Davis Information Center for the Environment. At DataLab, she applies geospatial tools to new avenues of research across disciplines.

Tyler Shoemaker is a Postdoctoral Scholar. He holds a Ph.D. in English Literature from UC Santa Barbara and conducts research on media history and the digital humanities. At the DataLab, Tyler develops and implements methods for text analysis and natural language processing across a variety of research projects, ranging from literary studies to environmental and health sciences.

Wesley Brooks is a research data scientist. He holds a PhD in Statistics and an MS in Biostatistics from the University of Wisconsin-Madison, where he taught as a lecturer before joining DataLab. He was a postdoc in the Ecostats lab at the University of New South Wales, studying point processes and ecological statistics. His interests span from statistical computing to spatial statistics, nonparametric regression, and multimodel inference.

Elise Hellwig is a research data scientist. She holds a BA in Mathematics from Colorado College and graduate degree in Ecology from UC Davis where she investigated spatial variation in climate impacts on California’s agriculture. Elise is dedicated to bringing rigorous data and statistics practices to new groups, from college students to the CA State government. Her interests include statistics, spatial data analysis and visualization, Bayesian regression, and natural language processing.

Nick Ulle is a statistician and computer scientist. He received a PhD and MS in Statistics from UC Davis, where he developed source code analysis techniques for the R programming language. He also received a BS in Mathematics from UC San Diego. He was a visiting assistant professor of Statistics at UC Berkeley, where he designed and taught courses in data science. His research interests include statistical computing, programming languages, data visualization, and pedagogy.

Oliver Kreylos is a computer scientist researching virtual reality and computer graphics, and their application to scientific data analysis. Kreylos received his PhD in Computer Science from UC Davis. He holds master’s degrees in Computer Science from UC Davis and the University of Karlsruhe, Germany. Kreylos developed the virtual reality user interface and research applications software for the UC Davis KeckCAVES and AR Sandbox.

Glenda Gaines holds a bachelor’s degree in Political Science from University of California, San Diego. “From the standpoint that all things are political—from the votes we cast, to the food we eat, to the shelter we seek—it is the art of governance that maintains the ability to not only define the human condition but improve upon it.” Glenda Gaines 

We’re hiring a graduate student to work at DataLab as a GSR for our immersive undergraduate education program. Applicants must have prior teaching experience and expertise in using the R programming language for applied research projects. Candidates can be from any graduate program or group at UC Davis, and must be available for both winter and springs quarter 2024. Contact us datalab-recruit@ucdavis.edu if you are interested in applying.

Professor Brown serves as DataLab’s Director for Community Engagement.  The Brown lab focuses on genomic, transcriptomic, and metagenomic sequence analysis. The lab is the primary developer of the khmer software, for faster and more efficient sequence analysis of high-throughput sequencing data. They also run quite a bit of training in data-intensive biology. Professor Brown serves on DataLab recruitment committees, teaches workshops, leads hackathons, and participates in our strategic activities and planning. His lab also runs the “Meet and Analyze (biological) Data” (aka MAD) weekly drop-in office hours.

Professor Filkov serves as DataLab’s Director for Translational Data Science.  He is a data scientist specializing in a number of applied areas including Empirical Software Engineering, Systems Biology and Gene Networks in Plants, Applied Network Theory, and Data Mining and Algorithms.

Professor Rajarantnam serves as DataLab’s Director for Research. He studies the theoretical and applied aspects of high dimensionality and extracting complex multivariate dependencies, including correlation-covariance estimation. His applied projects include applications in health and environmental sciences.