Conference Summary
The 2025 Section Meeting will be held at Idaho State University in Pocatello Idaho.
Registration
Registration Rates
$50 - University Faculty (Non-MAA Member)
$40 - University Faculty (MAA Member)
$20 - University Students, High School Teachers, and all others
Registration will be open up to the day of the conference and can also be done on-site. When registering online, you can also add on a dinner for the program/talk on Friday night ($35), a box lunch for Saturday ($12), and sign up for the “AI Essentials Workshop” conducted by Lew Ludwig (free, details below). Note that meal options need to be submitted by March 6!
IF YOU HAVE DIETARY RESTRICTIONS/PREFERENCES: Please choose the option closest to what you would prefer to eat. You will then have an opportunity to enter additional instructions to catering, and they will make a version of that meal that meets your instructions.
IDAHO STATE UNIVERSITY STUDENTS AND ISU DEPARTMENT OF MATHEMATICS & STATISTICS FACULTY: Please register using the email address math@isu.edu.
hotel options
Blocks of rooms have been reserved at the hotels below under the name “MAA Conference” for March 14 and 15. Both are just a couple miles from campus and include breakfast. Reservations at these hotels need to be made by March 1 to get the rate listed.
UPDATE (March 3): A block of rooms is still available at the price listed below at Towneplace Suites. These will remain available until Friday, March 7 or until sold out.
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151 Vista Dr., Pocatello, ID (208) 233-8200, #4
10 King and 10 Double Queen, conference rate is $104/night plus tax
To reserve call the local hotel number directly (208) 233-8200, then Option #4 (not the option 'to make a reservation').
(Cancellation policy: at least 24 hours ahead.)
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2376 Via Caporatti Dr. Pocatello, ID (208) 478-7000
20 rooms plus 10 King Suites, 7 Double Queen Suites, conference rate is $109/night plus tax
(Cancellation policy: at least 48 hours ahead)
Program and SCHEDULE
The schedule can now be found in the document linked below. Note that there are some minor changes from the schedule that was posted online previously.
Student Activity: Math/Stats Jeopardy
Any undergraduate students who are interested may participate. Sign-up will take place at the conference.
Invited Address: Allison Henrich, Seattle University
Title: How to Turn Your Knots from Blah to Fabulous
Abstract: Are you tired of tying boring old shoelace knots? Frustrated with messy knots in your spaghetti that are impossible to undo? Wish you could make friends and influence people with your amazing knot-tying ability? Join us and learn to harness the power of mathematics and the fourth dimension to unlock the secrets of knots.
Bio: Allison Henrich is a Professor of Mathematics at Seattle University and editor of MAA FOCUS, the newsmagazine of the MAA. She enjoys collaborating with students on research, especially on problems related to knots and games. She coauthored the books An Interactive Introduction to Knot Theory and A Mathematician’s Practical Guide to Mentoring Undergraduate Research, and she coedited the Euler Prize-winning book Living Proof: Stories of Resilience Along the Mathematical Journey. In 2024, she was excited to publish her most recent co-authored book, a tool for undergraduate math majors called Navigating the Math Major: Charting Your Course.
Invited Address: Emilie Purvine, Pacific Northwest National Laboratory
Title: Graphs and Hypergraphs and Topology, Oh My!
Abstract: Mathematical structures and concepts can be great models of real-world data. For example, differential equations have a long history of success in applied mathematics to model dynamics found in rivers and oceans, the atmosphere, and molecular systems (just to name a few!). Network science is an area of applied math that uses graph structures to model relational systems like social, collaboration, and transportation networks. Graphs, however, are limited to modeling pairwise relationships among entities. Hypergraphs and topological spaces provide alternate models of relational systems that allow for arbitrary sized and structured relationships. In this talk I will introduce the mathematical concepts of graphs, hypergraphs, and topology and show how they are used to model real-world data from a variety of applications including biological systems, chemistry measurements, and cyber networks. We’ll also talk about what measurements and properties of these structures can tell us about the systems they model.
Bio: Dr. Emilie Purvine is a mathematician and Chief Data Scientist at Pacific Northwest National Laboratory. She joined PNNL in 2011 after receiving her PhD in mathematics from Rutgers University with a focus on enumerative combinatorics and nonlinear recurrence relations. While at PNNL Emilie has had the opportunity to contribute to a variety of projects tackling hard problems in applications including computational biology and chemistry, power grid modeling, cyber network analysis, and knowledge models. Her current mathematical research focus is on topological data analysis applied to discrete structures like graphs and hypergraphs. Much of her work involves finding mathematical nuggets in applied domains and working on theoretical advances to enable operational progress.
Emilie also greatly values the ability to make mentoring a focus of her work. She loves to give presentations to students at all levels to provide an example of what a mathematician can do outside of academia. Interns and postgraduates (2-3 year temporary employees including post bachelors, post masters, and postdoc) are always included into her projects to promote on the job learning.
Outside of her core work activities Emilie has also been the chair of the MAA’s Membership Committee and an associate editor of the AMS Notices. In her free time Emilie spends time with her friends and family, enjoys a good book, loves the outdoors and traveling to new destinations.
WOrkshop: Lew Ludwig, Denison University
Title: AI Essentials: Getting Up to Speed for Informed Decisions
Overview: Are you hesitant about integrating AI into your courses? Uncertain how it can be utilized effectively in academia? You're not alone. Many educators feel overwhelmed by the rapid advancements in AI technology and its implications for teaching and research.
Workshop Details: Join us for a two-hour workshop designed to demystify AI and empower you with the knowledge to make informed decisions about its use. We'll start with an introduction to Large Language Models, explaining how they work and the ethical considerations they entail.
What to bring: Participants should bring a Wi-Fi-enabled laptop to fully engage in the hands-on portion of the workshop.
Hands-On Experience: The workshop will quickly pivot to a hands-on session with these AI models. You'll gain firsthand experience to understand their capabilities and limitations. This practical exposure is crucial for evaluating how AI can enhance your professional tasks—from developing course materials and improving annual reports to assisting in research tasks like literature reviews and grant proposal assessments.
Application in Education and Research: We'll explore potential applications of AI in academia, such as:
Creating personalized learning assistants for students.
Utilizing AI tools to streamline course content creation.
Leveraging AI for efficient research tasks such as literature reviews and vetting grant proposals.
Outcome: By the end of this workshop, you will have a clearer understanding of when and how AI can be beneficial in your teaching and research activities. You will also learn strategies to guide your students in the responsible use of AI tools.
Recommendation: While no prior experience with AI is required, participants are encouraged to consider a premium AI service like ChatGPT Plus, Claude Pro, or Gemini Advanced, each available at approximately $20/month. This investment will enable you to experience the full capabilities of advanced AI models during the workshop.
Please Note: This workshop acknowledges the practical limitations of controlling technology use outside the classroom. Instead of attempting to AI-proof assignments, we focus on informed usage and ethical considerations.
Bio: Lew Ludwig, Director of the Center for Learning and Teaching and Professor of Mathematics at Denison University, is recognized for his leadership in educational development, particularly in the integration of generative AI into higher education. He received the Distinguished Teaching Award from the Ohio Section of the Mathematical Association of America in 2013 and served as a project leader for the MAA Instructional Practices Guide, a resource promoting evidence-based instructional strategies in undergraduate mathematics education. With over 40 workshops to his credit, he has shared his expertise on both local and national stages. In 2021, he was honored with the POD Innovation Award for a pioneering faculty development program. Skilled in creating webinars and workshops, Lew is passionate about advancing mathematics education through innovative teaching methodologies and fostering inclusive learning environments.
IDAHO STATE TEACHING AND LEARNING SYMPOSIUM
An additional event, hosted by Idaho State University’s Program for Instructional Effectiveness, will be held on Friday, March 14 as well. For further information and registration, see their website. Zoom links will be available for those who register.