The talks will typically take place on Tuesdays at 4:00-5:00pm in Adel Room 164. Please contact Ye Chen if you would like to give a talk or have a question about the colloquium.
Date: Tuesday 9/8 at 4:00-4:50
Speakers: Samuel Harris, Assistant Professor, NAU
Abstract: The Smith-Ward problem originates in 1980 and is a problem about matrix ranges in operator theory. Matrix ranges are a tool sometimes used to understand the geometry of a bounded linear operator, while capturing underlying “statistics”. While there has been some progress over the years, the problem remained open in general until earlier this year when Marcel Scherer found a counterexample. In this talk we will strengthen this counterexample and show that a plethora of counterexamples exist that are not overly difficult to construct. Moreover, some counterexamples turn out to have rather exotic properties.
Date: Tuesday 9/15 at 4:00-4:50
Speakers: Angie Hodge-Zickerman, Professor, NAU
Abstract: This talk is adapted from Dr. Angie Hodge-Zickerman’s invited 2026 MAA MathFest Leitzel Lecture and explores the important role confidence plays in learning mathematics. Drawing on lessons learned across a wide range of university mathematics courses and mathematical learning experiences, Angie will share practical ways to help students build mathematical confidence while still engaging in challenging and meaningful mathematics. Participants will consider strategies for normalizing “not knowing yet,” creating opportunities for productive struggle, encouraging mathematical risk-taking, and helping students see themselves as capable mathematical thinkers. The session will invite us to consider how small shifts in our teaching can foster deeper engagement, persistence, and ultimately, greater joy in doing mathematics.
Date: Tuesday 9/22 at 4:00-4:50
Speakers: Jeffrey Covington, Data Scientist, NAU
Abstract: Bayesian filters are foundational algorithms for forecasting and prediction. They are the backbone of operational forecasting systems in many fields such as epidemiology, earth science, econometrics, and robotics, to name a few. This rich and active area of research admits many novel approaches, from dynamical systems to pure machine learning and AI, as well as hybrid strategies. First, we introduce Bayesian filtering including the foundational algorithms of the particle filter and ensemble Kalman filter. Next, we present cutting edge research in epidemiology: real-time week-to-week forecasting of influenza hospitalizations. Finally, we highlight promising areas of research and trends across the field of Bayesian filtering, perhaps inspiring discussion and future research.
Date: Tuesday 9/29 at 4:00-4:50 (Online)
Speakers: Tom Edgar, Assistant Professor, CSU
Abstract: TBD
Date: Tuesday 10/13 at 4:00-4:50
Speakers: Jeffrey Downard, Associate Professor, NAU
Abstract: TBD
Date: Tuesday 10/20 at 4:00-4:50
Speakers: Mike Falk, Professor Emeritus, NAU
Abstract: TBD
Date: Tuesday 10/27 at 4:00-4:50
Speakers: TBD
Abstract: TBD
Date: Tuesday 11/10 at 4:00-4:50
Speakers: Kiona Ogle, Professor, NAU
Abstract: TBD
Date: Tuesday 11/17 at 4:00-4:50
Speakers: Keegan Line, Graduate student, NAU
Abstract: TBD