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NSF Research Experience for Undergraduates

Are you interested in data-driven next-generation bioinformatics and data science analysis? Interested in developing and coding the state-of-the-art computational approaches and algorithms for big data analysis on genomic data? Interested in the discovery that comes from an interdisciplinary approach to science?  Our vision for the NSF Research Experience for Undergraduates (REU) site is to cultivate the talents of an intellectually and culturally diverse group of 10 undergraduate students each year drawn from fields related to the life science, bioinformatics, and computer science by engaging them in ongoing biological research projects that employ next-generation DNA sequencing technologies and high performance computing. This is the Omics Experience.

Research Labs and Faculty


Data Science Research Lab

The Anderson Data Science Research Lab develops algorithms and software to tackle some of the most challenging and interesting big data problems in the life sciences. Our research interests include pattern analysis in high-dimensionality data sets, evolutionary computation and optimization, machine learning, data science, computational genomics, cloud computing, computational metabolomics, and eScience. We currently have multidisciplinary projects underway in metabolomics, human cognition, toxicology, marine biology, and medical genomics.

For more information, please contact Paul Anderson.

Jason Howell

Numerical methods for ordinary and partial differential equations

Much of my research involves finding new numerical techniques for computing approximate solutions to ordinary and partial differential equations.  I enjoy working on all kinds of problems in computational mathematics and numerical analysis.  I am also interested in applications of differential equations in many different areas of science, with a particular interest in equations that describe the flow of a Newtonian or non-Newtonian fluid.