2026 REU Mentors

Andrea K. Barreiro, Ph.D., is an Associate Professor of Mathematics at SMU. Her research interests span a range of applied math topics, including fluid dynamics, neuroscience, and social science. In neuroscience, Dr. Barreiro has made contributions to understanding how neural network mechanisms function to store and transmit information, and to developing novel statistical tools for identifying neural clusters and to characterize critical dynamics; her recent work has been funded by the National Science Foundation (NSF) and National Institutes of Health (NIH). In social science, Dr. Barreiro is working in voting and electoral policy; together with colleagues at SMU she spearheaded a project to track the 2021 redistricting process in the Texas Legislature, using innovative analyses and visualizations to document partisan and racial gerrymandering (www.smu.edu/mumtx).  Most recently, she is collaborating on projects (www.ncvr.org and a related Substack) to translate data analysis into actionable insights for voters. Andrea received a BS and MS from Rensselaer Polytechnic Institute, and her Ph.D. in Mathematics from New York University. Before arriving to SMU, she did postdoctoral training at the University of Illinois and the University of Washington. 

REU Project

This initiative will explore the use of topological data analysis, including persistent homology (PH), to evaluate access to infrastructure resources like grocery stores, libraries, or voting sites. Recently, a group at SMU (Li et al., Cities, 2022) documented infrastructure deserts in the City of Dallas by gathering data on 13 types of infrastructure. This exhaustive effort requires time- and space-intensive data collection: for resources at discrete points (such as grocery stores), this process included itemizing every residential property in the city and measuring distance to the closest resource. For such discrete point resources (such as grocery stores), persistent homology offers an alternative framework to quantify access which requires only the resource locations themselves, not the locations of the persons accessing them. Furthermore, PH can be used to provide gradated estimates of accessibility (e.g. resource within 10 minutes vs. 11 minutes vs. 30 minutes). Students will develop a pipeline to apply PH tools to discrete resource locations, using Dallas County grocery stores as a proof-of-concept example. We will use this pipeline to quantify “holes” in resource coverage and explore the possibility of optimizing the addition or removal of resources. 

Anthony J. Petrosino, Ph.D., is Professor of Teaching and Learning in the Simmons School of Education and Human Development at SMU and Professor Emeritus at The University of Texas at Austin. A nationally recognized scholar in the Learning Sciences and STEM Education, Dr. Petrosino’s research examines how people learn in authentic, problem-rich environments—classrooms, communities, and immersive digital spaces—and how those insights can inform equitable and effective educational practice at scale.

REU Project

This initiative is dedicated to leveraging data science to address issues of food justice, focusing on identifying and addressing food deserts in underserved communities. Students involved in the project will begin by creating predictive models using American Community Survey (ACS) data. They'll analyze indicators of low mobility and income levels to pinpoint potential food deserts within these communities. Using mapping tools, students will then compare their predictive models with real-world data on food deserts, gaining insights into the spatial distribution of food insecurity. Finally, students will utilize webscraping methods to locate and map urban farms. This will help determine if these essential resources are strategically positioned to serve populations in low-income, low-mobility areas.

Janille Smith-Colin, Ph.D., is an Associate Professor of Civil and Environmental Engineering at SMU. She specializes in the sociotechnical systems analysis of multimodal transportation projects, using quantitative, spatial, and data-driven methods. Her research advances sustainability and resilience by investigating disparities in mobility across population subgroups under both normal operations and hazard conditions. She further examines the role of emerging transportation technologies in improving access to opportunities. She has led projects funded by the National Institutes of Health, the U.S. Department of Transportation, and the National Institute of Standards and Technology, and has published in peer-reviewed journals including Journal of Transport Geography, Transportation Research Record, and Transportation Research Parts A and D. Dr. Smith-Colin has served on standing committees of the Transportation Research Board and the American Society of Civil Engineers, and she is a licensed Professional Engineer.

REU Project

Students will engage in building a custom AI-assisted case study library for the infrastructure (in)justice framework. Students will work with real-world infrastructure data—case studies, planning documents, community reports, academic literature, and policy analyses—to understand how infrastructure projects produce unequal benefits and burdens. By structuring these case studies into an AI-supported database, the project will: identify patterns of infrastructure development relevant to Dallas (e.g., highway impacts, transit access, historical disinvestment), support evidence-based discussions of restorative and reparative strategies, and create a scalable analytical tool that helps planners, educators, and community partners evaluate the implications of future infrastructure decisions. This contributes to broader local and national efforts to design community-centered infrastructure.

 

Beth Wheaton-Páramo, Ph.D., is a research assistant professor and senior lecturer in economics at SMU. She is a researcher on child labor and the economics of human rights, including capital punishment, violence against women, seeking asylum, terrorism, child abuse, genocide, hate, and human trafficking. She was the principal investigator on a $1.187 million U.S. federal grant from the Department of Justice (DOJ) National Institute of Justice (NIJ), which provided the foundation for building the SMU Human Trafficking Data Warehouse. She is team lead on the SMU Human Trafficking Data Research (HTDR) Project with its goal to Make Human Trafficking Data Work. She published The Economics of Human Rights in 2018, the first textbook on applying economic theory and tools to understanding human rights issues. Beth holds an MA and PhD in economics from Temple University, an MS in international business and trade from Grambling State University, and BBA from Sam Houston State University. 

REU Project

In 2022, Southern Methodist University (SMU) was awarded a $1.187 million federal earmark grant from the Department of Justice. The SMU Human Trafficking Data Research (HTDR) Project was created to work as an independent agency to coordinate expertise from all areas of anti-trafficking to build expert research teams to solve issues related to human trafficking. This Project invests in building expertise to drive effective research, policy making, and practice. SMU provides secure servers to securely house and protect sensitive human trafficking data. Users of the data warehouse will be granted specific security clearances to access data for analysis. This data allows practitioners and policymakers to run statistical reports and trends and to make new connections involved in human trafficking.

Eric Godat, P.h.D., is the Director of Research Technology Services in the Office of Information Technology. He and his team support numerous research projects across all campus disciplines by leveraging high-performance computing (HPC), internet of things (IoT), AI/machine learning, and data science. Dr. Godat's passion for research and expertise in data science and HPC were developed during his doctoral work here at SMU in theoretical particle physics where he studied nuclear parton distribution functions. Prior to that he did his bachelor's in physics and mathematics at Southwestern University.

Marc Sager, M.S., is a Ph.D. Candidate in the Department of Teaching and Learning in Simmons School of Education and Human Development at Southern Methodist University. His research focuses on learning in data science education, informal STEM learning, and research-practice partnerships. He has worked on several National Science Foundation funded research projects in many capacities, from data collection and analysis to dissemination. Before pursuing his graduate degree, Marc worked in food production and agricultural sales and taught secondary agricultural sciences in formal and informal contexts. His research continues to span across both in-school and out-of-school learning environments. Marc teaches courses on topics within the learning sciences and is active in the education research community through service on committees.

Mateo Langston Smith is a mid-level Data Analyst in the Office of Information Technology at SMU. He played the key role of Data and Visualization Analyst for the $1.187 million NIJ Human Trafficking Project grant to build the SMU Human Trafficking Data Warehouse, which is the foundation for the SMU Human Trafficking Data Research (HTDR) Program. His work focuses primarily on structuring, analyzing, and building applications to display data effectively. He has spent the last 5 years building his data science and application development skills through multiple projects across the fields of biology, health sciences, sports, religion, and human trafficking. He has served as a Data Science Consultant for larger projects, including a data processing project with Lawrence Livermore National Laboratory. Mateo received a B.S. in Mathematics and Computer Science from Biola University in 2022.

Dr. Monnie McGee is an Associate Professor in the Department of Statistics and Data Science and Principal Investigator for the Data Science for Social Good REU. She earned a B.A. in Mathematics and English from Austin College in Sherman, Texas, and M.A. and Ph.D. degrees in Statistics from Rice University. She specializes in sports analytics, particularly analysis of “individual-team” sports like track & field, swimming & diving, and gymnastics. She has also done work on the analysis of high-throughput biological data and the comparison of the performance of generative AI algorithms on statistics exams. For all the applications previously mentioned, she has applied and developed methods for compositional data analysis, particularly those methods using the Nested Dirichlet Distribution and related distributions. Dr. McGee has developed and taught many courses in statistics at the graduate and undergraduate levels at SMU, including several full programs, such as a Master of Science in Data Science (MSDS), and Bachelor of Data Science (BSDS), and Master of Data Science and Applied Statistics (MDSAS).  Her courses and proposals reflect her practice in creating an active learning environment in the classroom, regardless of the course level. Her goal is to help students and the community become citizen statisticians and data scientists through her work in higher education and her contributions to the scientific literature.

Dr. Jennifer Ebinger, EdD, is the Senior Director of the Office of Engaged Learning and a Principal Investigator for the Data Science for Social Good Research Experience for Undergraduates. In her role as Senior Director, she leads experiential learning initiatives, fostering out-of-the-classroom experiences in research, entrepreneurship, and high-impact educational practices. With over 25 years of experience in leadership, education, organizational change consulting, and program development, Jennifer has a proven track record of implementing innovative learning solutions that drive organizational success. She holds a Doctorate in Higher Education, a Master’s in Teaching, and boasts extensive consulting and coaching experience.