University of Montana
Social Sciences 401
Missoula, MT 59812
Phone: (406) 243-2883
Yolanda Reimer, Professor
Broadening CS in High Schools
The focus of this project is to broaden the computer science curriculum available in Montana's public high schools so that more students are exposed to opportunities within CS. Educators from the University of Montana, Montana Tech, Montana State University and Salish Kootenai College have formed a statewide collaboration to increase the number of teachers qualified to teach computer science in the state, and to engage more high school students in various topics and activities within CS. To achieve these goals we are:
- Preparing high-school teachers to teach CS topics by offering multiple professional development opportunities.
- Providing hands-on and online resources for on-going professional development.
- Establishing a community of CS K12 teachers around the state .
- Focusing on engaging underrepresented groups, women and Native Americans in particular.
- Using an educational research foundation to build, assess, and inform our on-going activities.
Rob Smith, Assistant Professor
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
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.
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.