Katie Morrison, Ph.D.

PhD, University of Nebraska, 2012.
Area of Study: Mathematics, Minor in Electrical Engineering
Thesis: Equivalence and duality for rank-metric and matrix codes
Advisor: Dr. Judy Walker

MS, University of Nebraska, 2008.
Area of Study: Mathematics

BA, Swarthmore College, 2005.
Area of Study: Mathematics and Psychology

Professor, University of Northern Colorado
Department of Mathematical Sciences (2023 – Present)

Associate Chair, University of Northern Colorado
Department of Mathematical Sciences (2022 – Present)

Associate Professor, University of Northern Colorado
Department of Mathematical Sciences (2017 – 2023)

Assistant Professor, University of Northern Colorado
Department of Mathematical Sciences (2012 – 2017)

Research Associate, Pennsylvania State University
Department of Mathematics (2015)

Algebraic Coding Theory

I’m interested in how algebraic and discrete structures can be used to support efficient transmission and storage of information.

Mathematical Neuroscience

I work on mathematics questions arising from theoretical neuroscience, particularly neural network theory and neural coding. I’m interested in applications of linear algebra, abstract algebra, and discrete math.

Google scholar profile  

• Morrison, K., Degeratu, A., Itskov, V., Curto, C. (2024). Diversity of emergent dynamics in competitive threshold-linear networks. SIAM Journal on Dynamical Systems, 23(1), 855-884.. DOI: https://doi.org/10.1137/22M1541666
• Curto, C., Morrison, K. (2023). Graph rules for recurrent network dynamics. Notices of the American Mathematical Society, 70(4).
• Curto, C., Geneson, J., Morrison, K. (2023). Stable fixed points of combinatorial threshold-linear networks. Advances in Applied Mathematics, 154.
• Parmelee, C., Moore, S., Morrison, K., Curto, C. (2022). Core motifs predict dynamic attractors in combinatorial threshold-linear networks. PLOS ONE, 17, 1-21.
• Parmelee, C., Alvarez, J. L., Curto, C., Morrison, K. (2022). Sequential attractors in combinatorial threshold-linear networks. SIAM J. Appl. Dyn. Syst., 21(2), 1597-1630.
• Curto, C., Morrison, K. (2019). Relating network connectivity to dynamics: opportunities and challenges for theoretical neuroscience. Curr Opin Neurobiol, 58, 11-20.
• Curto, C., Gross, E., Jeffries, J., Morrison, K., Rosen, Z., Shiu, A., Youngs, N. (2019). Algebraic signatures of convex and non-convex codes. J. of Pure and Appl. Algebra.
• Curto, C., Geneson, J., Morrison, K. (2019). Fixed Points of Competitive Threshold-Linear Networks. Neural computation, 31(1), 94-155.. DOI: https://doi.org/10.1162/neco_a_01151
• Burzynski, A., Anderson, S., Morrison, K., Patrick, M., Orr, T., Thelan, W. (2018). Lava lake thermal pattern classification using self-organizing maps and relationships to eruption processes at Kīlauea Volcano, Hawaii.. DOI: https://doi.org/10.1130/2018.2538(14)
• Curto, C., Gross, E., Jeffries, J., Morrison, K., Omar, M., Rosen, Z., Shiu, A., Youngs, N. (2017). What makes a neural code convex? SIAM J. Appl. Algebra and Geometry, 1, 222-238.
• Curto, C., Morrison, K. (2016). Pattern Completion in Symmetric Threshold-Linear Networks. Neural computation, 28(12), 2825-2852.. DOI: https://doi.org/10.1162/NECO_a_00869
• Gluesing-Luerssen, H., Morrison, K., Troha, C. (2015). Cyclic Orbit Codes and Stabilizer Subfields. Advances in Math. of Commun., 9(2), 177-197.
• Morrison, K. (2015). Enumeration of Equivalence Classes of Self-Dual Matrix Codes. Advances in Math. of Commun., 9(4), 415-436.