Research Projects

Yolanda Reimer, Professor

NSF CS10K Project

The rising demand for graduates with computer related skills is projected to be among the fastest growing fields between 2012-2022, and many of those jobs are among the highest paying in the nation. In the state of Montana, these same trends are evident. The focus of this project is to increase the number of students graduating with degrees in CS, and subsequently to increase the number of skilled young people who are able to live and work in the state of Montana—a result that would certainly boost its overall economy.

In this NSF funded project, we are expecting to achieve the following goals:

  • Broaden the CS curriculum available in Montana's public high schools so that more students are exposed to opportunities within CS
  • Increase the number of qualified computer science teachers in the state
  • Engage more high school students with various topics and activities in computer science.

Rob Smith, Assistant Professor

Mass Spectrometry

Mass spectrometry is a critical tool for identifying and measuring chemical compounds in samples, information that is used in drug design, disease diagnosis, and many other applications. Current technology is limited in the accuracy of measurements and the quantity of compounds that can be detected, limiting contributions to these applications. The Smith lab develops advanced algorithms, interfaces, and backend infrastructure for computational mass spectrometry, leveraging computer science techniques to enable the analysis of significantly more compounds than current methods. The lab typically employs a large number of student researchers at the graduate and undergraduate level from computer science, biochemistry, and statistics.

Travis Wheeler, Assistant Chair of Computer Science

Computational Genomics

Our group develops methods in computational biology, with an emphasis on genomic sequence analysis. For the most part, that involves development of algorithms that increase the speed, power, and accuracy of methods for comparing biological sequences, using a mix of information theory, algorithm design, and software/hardware optimization. We also apply these methods to biology-motivated topics, especially those involving transposable elements and regulatory elements.

Human genome sequencing process

Alden Wright, Emeritus Professor


Humans are a technological species. Over the last 3 million years our evolution has been profoundly shaped by the things we make and use, which in turn have been impacted by the cultural abilities that humans possess. While we can no longer claim that either technology or culture is unique to humans, we do know that human abilities in these two areas are more complex than those of other species. Our cultural capacity allows us to store and transmit the knowledge and skills necessary to refine and innovate technologies, and in doing so to build on the advances made by the countless generations that have gone before us.

Researchers now see that human biology and culture are complexly connected, and that we can often understand the evolution of both culture and technology as processes that have analogies in biological evolution. This enables researchers to use theory and methods drawn from the biological sciences in order to understand cultural and technological change, and provides a powerful interdisciplinary approach to the study of human evolution.