AWM at MathFest 2024

August 7 − August 10, 2024,  Indianapolis

All times are Eastern Daylight Time

AWM − MAA Etta Z. Falconer Lecture: Towards Fairer-ness in Machine Learning

Deanna Needell, University of California, Los Angeles
Time and place TBD

In this talk, we will address several areas of recent work centered around the themes of transparency and fairness in machine learning as well as highlight the challenges in this area. We will discuss recent results involving linear algebraic tools for learning, such as methods in non-negative matrix factorization that include tailored approaches for fairness. We will showcase our derived theoretical guarantees as well as practical applications of those approaches. These methods allow for natural transparency and human interpretability while still offering strong performance. Then, we will discuss new challenges and directions in fairness including an example in large-scale optimization that allows for population subgroups to have better predictors than when treated within the population as a whole.  Throughout the talk, we will include example applications from collaborations with community partners, using machine learning to help organizations with fairness and justice goals.

AWM-MAA Invited Paper Session (aligned with the Falconer Lecture)
Iterative and Sketching Approaches for Linear Systems and Beyond

Time and Place TBD

Iterative and sketching approaches play crucial roles in solving linear, convex, and even non-convex systems, offering different strategies for handling various types of problems. Iterative methods involve repeatedly refining an initial guess for the solution until it converges, and often act on small amounts of data at a time, making them amenable to large-scale and/or sparse problems.  Sketching approaches, often inspired by techniques from signal processing, provide a more efficient way to approximate solutions in situations where the system is overdetermined or ill-conditioned. They reduce the computational burden by sampling or sketching the input data, thus making it feasible to solve systems that would be computationally infeasible using traditional methods. Both approaches offer valuable tools in the realm of linear system solvers and beyond, allowing for flexibility in choosing the most suitable method depending on the problem’s characteristics and computational resources available. Work on these methods, their applications, their theoretical underpinnings, and their connections to machine learning are welcome.


A Multiplicative Algorithm for Curvature Corrected Semi non-negative Matrix Factorization of Manifold-valued Data
Joyce Chew, University of California, Los Angeles

Randomized Kaczmarz Method for Linear Discriminant Analysis
Jocelyn Chi, Rice University

Variable Projection Methods for Large-scale Separable Nonlinear Inverse Problems
Malena Español, Arizona State University

Tensor Completion for Low CP-Rank Tensors via Random Sampling
Santhosh Karnik, Michigan State University

Stochastic Iterative Methods for Online Rank Aggregation from Pairwise Comparisons
Lara Kassab, University of California, Los Angeles

Randomized Gauss-Seidel and Column-Slice-Action Methods for Tensor Problems
Alona Kryshchenko, California State University Channel Islands

Iterative Approaches for Tensor Linear Systems
Anna Ma, University of California, Irvine

Kaczmarz based Iterative Hard Thresholding Techniques for Low-Rank Tensor Recovery
Shambhavi Suryanarayanan, Princeton University

Robust, Randomized Preconditioning for Kernel Ridge Regression
Robert Webber, California Institute of Technology

How to Hire a Math Educator: Considerations for Mathematics Departments

This panel brings together mathematicians and mathematics educators to discuss the challenges that mathematics educators face when working in mathematics departments that do not have mathematics education research as part of their portfolio. Our panelists will jointly discuss aspects of the challenges that mathematics departments will need to address in order to sustain collegial and productive interactions among faculty.

Vilma Mesa, University of Michigan
Rachel Chaphalkar, University of Wisconsin-Whitewater
Raechel Kenney, Purdue University
Elsa Medina, Cal Poly San Luis Obispo
Dante Tawfeeq, John Jay City University of New York

Vilma Mesa, University of Michigan

Education Committee of the Association of Women in Mathematics

Mental Health in the Mathematics Community: Continuing the Conversation

This panel addresses the mental health of faculty, students, and others in the mathematics community. Strategies for individuals and groups will be shared, and progress will be highlighted. Panelists contribute diverse perspectives as faculty members, researchers in the emotional aspects of mathematics, and mental health professionals. We anticipate an open and empathetic dialogue to improve the well-being of our community.

Janet Fierson, La Salle University
Buna Sambandham, Utah Tech University
Jeanette Shakalli, Panamanian Foundation for the Promotion of Mathematics (FUNDAPROMAT)
Mariana Smit Vega Garcia, Western Washington University

Association for Women in Mathematics (AWM)

AWM Student Chapter Awards – with Dessert!

Time and Place TBD

Each year the AWM recognizes outstanding achievements in chapter activities among the AWM Student Chapters. Awards will be given in four categories: (1) community outreach; (2) fundraising and sustainability, (3) professional development, and (4) scientific excellence. These awards will be given out at the MAA Student Dessert Reception on Friday night. Come celebrate with us!

Visit the AWM Booth in the Exhibit Hall

Swing by the virtual AWM booth, buy a t-shirt, get some AWM swag, learn about the many programs AWM has to offer and meet other AWM’ers! Are you interested in volunteering your time at the booth? Email to volunteer.