Vice Chancellor for Academic Affairs
HHMI and Distinguished McKnight University Professor
Director, Center for Learning Innovation
Director of Graduate Studies, Biomedical Informatics and Computational Biology
University of Minnesota, Rochester
Ph.D. (Mathematics), Cornell University, 1990
As Vice Chancellor for Academic Affairs, I am responsible for the development of academic programs on the new campus of the University of Minnesota in Rochester. In Fall 2008, we launched an all-University, interdisciplinary graduate program in Biomedical Informatics and Computational Biology (BICB) between the University of Minnesota Twin Cities and the University of Minnesota Rochester with faculty from the University of Minnesota Twin Cities, the University of Minnesota Rochester, the Hormel Institute, Mayo Clinic, and IBM. The graduate program trains graduate students in the development and applications of computational methods and to work in interdisciplinary teams of life scientists and computational scientists. The administrative home of the BICB graduate program is at UMR and I serve as the Director of Graduate Studies of this program.
The University of Minnesota Rochester launched a new baccalaureate degree program, the Bachelor of Science in Health Sciences (BSHS), that provides education and training for students interested in Health Professions career programs, graduate education, and professional degrees. This program and its faculty are housed in the Center for Learning Innovation. The Center promotes a learner-centered, technology-enhanced, concept-based, and community-integrated learning environment in which ongoing assessment guides and monitors student achievement of measurable objectives and is the basis for data-driven research on learning. I serve as the director of this center.
Biomedical Informatics and Computational Biology; Mathematics; Bioinformatics; Ecology, Evolution, and Behavior; Conservation Biology; Stream Restoration Science and Engineering.
Theoretical ecology; role of space in community dynamics; theoretical population genetics; coalescent theory; assessment and learning.
I am an applied mathematician. My research interests span areas of biology across levels of organization, from the genome to ecological communities. Specifically, I study the role of space in community dynamics, investigate how selection affects genealogies, and develop statistical tools for genomics research. These investigations are theoretical, relying on mathematical models, analytical methods, and partially on computer simulations. As part of the development of the Bachelor of Science in the Health Sciences, I am developing assessment tools and assessment software to closely track student learning in this program and to build a rich data set that can be mined to build predictive models of student learning.
When I joined the School of Mathematics at the University of Minnesota Twin Cities in 1996, I developed a calculus course for biology majors (MATH 1281 and MATH 1282). This resulted in a text book, Calculus for Biology and Medicine (Prentice Hall), which is now in its third edition. When I moved from Mathematics to the department of Ecology, Evolution and Behavior at the University of Minnesota Twin Cities, I wanted to continue my educational efforts. With support from the Howard Hughes Medical Institute, I am now developing ways to improve the quantitative training of biology majors by integrating mathematics and statistics directly into biology courses. This has resulted in a number of resources.
I moved to the University of Minnesota Rochester in 2008 to lead the development of the Bachelor of Science in Health Sciences and to develop a personalized learning approach. This new degree program offers the opportunity to develop new pedagogies for integrating knowledge across disciplines. This will enhance student learning and lead to a deeper understanding. With funding from the Howard Hughes Medical Institute, I am developing the quantitative part of the curriculum.
C. Neuhauser and S. Krone 1997. The Genealogy of Samples in Models with Selection. Genetics 145:519-534.
C. Neuhauser and S. Pacala 1999. An explicitly spatial version of the Lotka-Volterra model with interspecific competition. Annals of Applied Probability 9:1226-1259
C. Neuhauser 2000. Mathematical Models in Population Genetics. In Handbook of Statistical Genetics. Pp. 153-178. Wiley.
P. Chesson, S. Pacala, and C. Neuhauser 2002. Environmental niches and ecosystem functioning. In Biodiversity and Ecosystem Functioning. Pp. 213-245. Princeton.
C. Neuhauser, D.A. Andow, G. Heimpel, G. May, R. Shaw, and S. Wagenius 2003. Community Genetics - A Synthesis of Community Ecology and Population Genetics. Ecology 84: 545-558.
C. Neuhauser and J. Fargione. 2004. A mutualism-parasitism continuum model and its application to plant-mycorrhizae interactions. Ecological Modelling 177: 337-352 N.
Lanchier and C. Neuhauser. 2006. Stochastic spatial models of host-pathogen and host-mutualist interactions I. Annals of Applied Probability 16: 448-474.
N. Lanchier and C. Neuhauser. 2007. Voter model and biased voter model in heterogeneous environment. Journal of Applied Probability 44: 770-787.
E.K. Hall, C. Neuhauser, and J.B. Cotner. 2008. Toward a mechanistic understanding of how natural and bacterial communities respond to changes in temperature in aquatic ecosystems. The ISME Journa, February. Doi: 10.1038/ismej.2008.9.
N. Lanchier and C. Neuhauser. 2009. Spatially explicit, non-Mendelian diploid model. Annals of Applied Probability 19: 1880-1920.
M. Altun, M.D. Riedel, C. Neuhauser. Nanoscale digital computation through percolation. DAC 2009: 615-616.