2024-2025 SIAM EDI Change Agents

December 09, 2024

SIAM is excited to announce its selection of SIAM EDI Change Agents. The program is intended to provide a platform for SIAM members to engage in equity, diversity, and inclusion initiatives in a variety of areas including workplace practices, teaching, and research. Change agents seek to leverage their capacities as individuals (researchers, educators, and students) to contribute to improving equity, diversity, and inclusion among the broader SIAM community. The change agents have been awarded up to $2,500 for work that helps support this effort.

The 2024-2025 EDI Change Agents are:

Alejandra Castillo, Pomona College, U.S. and Christina J. Edholm, Scripps College, U.S.
Anastasiia Minenkova, University of Hartford, U.S.
Elizabeth Newman, Emory University, U.S. and Elizabeth Qian, Georgia Institute of Technology, U.S.
Ruth Alejandra Torres-Rubiano, Fundación Universitaria Konrad Lorenz, Colombia

Alejandra Castillo
Pomona College, U.S.

Alejandra Castillo teaches mathematics and statistics at Pomona College. She is also an alumnus of the Pomona College Academy for Youth Success (PAYS), an ongoing college access program that has strong ties in the Los Angeles and San Bernardino regions. As a statistician, she is intrigued by utilizing data and statistical methodology to answer questions in the fields of biology and public health. She is interested in introducing students to statistical computing and careers in statistics. In the past, she has mentored REU programs and college access programs. She is invested in creating mutually beneficial partnerships between academia and local organizations. At the Claremont Colleges, she is involved with the AWM chapter and the community for first-generation/Low-Income students.

Christina J. Edholm
Scripps College, U.S.

Christina Edholm is an assistant mathematics professor at Scripps College, who advises on computer science and data science as well. She did her undergraduate at Willamette University, then went on to do her master’s and Ph.D. at the University of Nebraska-Lincoln, where she started working in applied mathematics. One side of her research still focuses on control theory and invasive species from her Ph.D. work, while she has also branched into infectious disease modeling. Through a variety of programs, she has worked on numerous infectious disease models, using different mathematical techniques and analysis. She is actively engaging in research now through these ongoing collaborations and with her undergraduate students. Her research also influences her teaching, and she incorporates her own work and findings into courses. Learn more Professor Edholm’s work

The recipients collaborated on their answers to our questions.

Why did you apply to the SIAM EDI Change Agents Program and what are you most looking forward to?

The opioid epidemic has affected millions of people, and with the rise of fentanyl overdoses more insight is needed into the epidemic and potential strategies going forward. After attending a meeting of the Inland Empire Opioid Crisis Coalition (IEOCC), we want to utilize mathematical modeling to study fentanyl usage and overdoses, for specific locations and behavioral dynamics, considering management options. With this new connection, we were interested in connecting more in the community to use our skills to give insight into this devastating situation. We applied for the SIAM EDI Change Agents Program to engage with students on research while also building something to share with the general public.

Castillo: I am very excited to work with high school and undergraduate students on a project that is very relevant to the local community. I look forward to introducing students to methods used in mathematical biology to answer questions that arise in public health. I think students will not only benefit from learning mathematical tools, but also from being part of a collaboration with a local nonprofit interested in using math to answer their questions.

Edholm: Like Alejandra, I am excited for the opportunity to work with students, along with connecting with public health officials more. I think this project can bridge a variety of important areas for the opioid epidemic, and result in engaging materials for academics and the public.

Tell us about the project you will be working on as a SIAM EDI Change Agent.

For our project, we plan to introduce a cohort of early-stage college students and high school students to the field of applied mathematics through a project in mathematical biology. Our project will involve analyzing data collected from San Bernardino County on opioid usage. Students will learn about the mathematical models used to understand the opioid epidemic, and then analyze the models using analysis, statistical techniques, and numerical simulations. We have a variety of questions we plan to explore on this topic, which spans from data analysis to mathematical computations. There are the demographic implications of the data, and considering statistical measures, along with building on the literature of mathematical models. We plan to communicate our findings, both through academic channels and to the public. Lastly, beyond exposing students to this area of mathematics for the first time, we also want to share with them the careers and resources available to them in the mathematical sciences.

Anastasiia Minenkova
University of Hartford, U.S.

Anastasiia Minenkova is an assistant professor at the University of Hartford, specializing in applied mathematics and numerical analysis. She earned her Ph.D. in mathematics from the University of Connecticut in 2022. Following her graduation, she served as a Visiting Lecturer at Mount Holyoke College for a year. Her research focuses on the stability of matrix decompositions on the intersection of numerical analysis and perturbation theory. Perturbation theory examines how slight modifications in mathematical models can influence their outcomes, which is crucial for developing robust algorithms. Recently, she has expanded her research to explore the applications of linear algebra in quantum computing. This emerging field leverages the principles of quantum mechanics to perform computations that are infeasible for classical computers.

Why did you apply to the SIAM EDI Change Agents Program and what are you most looking forward to?

This program would help my efforts to popularize mathematics and to attract, support, and keep students in mathematics from a diverse pool of talent, to create and sustain the safe and respectful campus environment that promotes academic success and prepares students for productive careers in BIG or graduate school. In addition, there are meta objectives: reducing bias affecting professional decisions, addressing historical disparities in mathematical sciences, ethical issues in mathematical research, introducing resources on equity and inclusion to a wider audience. As a part of this project, I plan to set up the Mathematics EDI Community Library in the lounge next to the Department of Mathematics at the University of Hartford. This library will feature about 20 carefully selected titles, ensuring that these valuable resources are accessible to all.

Elizabeth Newman
Emory University, U.S.

Elizabeth Newman is an assistant professor at Emory University in mathematics. Her research in computational mathematics falls broadly into two categories: extending numerical linear algebraic tools to multilinear algebra and developing efficient optimization methods for machine learning. She earned her Ph.D. and M.S. in mathematics from Tufts University and B.S. in mathematics and statistics from Haverford College.

Elizabeth Qian
Georgia Institute of Technology, U.S.

Elizabeth Qian is an assistant professor at Georgia Tech with a joint appointment in aerospace engineering and computational science and engineering. Her research develops computational and mathematical methods that accelerate and improve engineering design and decision-making, building on her interdisciplinary background. She holds S.B. and S.M. degrees in aerospace engineering and a Ph.D. in computational science and engineering, all from Massachusetts Institute of Technology.

The recipients collaborated on their answers to our questions.

Why did you apply to the SIAM EDI Change Agents Program and what are you most looking forward to?

Both of us are passionate about creating undergraduate research opportunities that enable students to gain practical insight into the real-world applicability of mathematics. However, we observed that there was a high barrier to entry for undergraduate students interested in applied and computational mathematics research; many research projects require students to have completed advanced math coursework and to have strong programming skills. We were excited to have the opportunity to apply for SIAM support and develop a model for undergraduate computational math research with lower barriers to entry. We also saw this as an opening to broaden engagement and create a community of diverse, enthusiastic students to learn new mathematical and computational skills collaboratively.

Tell us about the project you will be working on as a SIAM EDI Change Agent

We’re running a pilot undergraduate research program that targets students with no or minimal background in programming and college-preparatory mathematics. Our goals are (1) to teach applied and computational math research skills, including mathematics knowledge, programming, and computational and theoretical inquiry, within contexts that are accessible to students at early stages of their undergraduate careers; and (2) to foster community among our participants, both to support them in succeeding in their undergraduate studies generally and to demonstrate that research is fundamentally a community enterprise. Our first cohort consists of four first-year students comprising two teams, each consisting of one student from Emory University and one from Georgia Institute of Technology. Each team has an associated project related to uncertainty quantification and neural networks. The projects encompass probability, calculus, and linear algebra, all with computational components.