Graduate Student Association (GSA)

Lindsey Insco holds a Bachelor of Science in Chemistry from Xavier University (2022) and a Master of Science in Criminal Justice from the University of Cincinnati (2023). Lindsey is currently a doctoral student in Criminal Justice at the University of Cincinnati. Her research examines life-course patterns of offending, drug overdose trends and response efforts, and broader characteristics of terrorism and counterterrorism. 

Esnart is an international doctoral student in the college of education.  Her program concentration is  education community-based action research. Her research interests revolve around the intersection of early childhood education, emergency education, and the rights of girls.

Amota Ataneka Merang is a doctoral candidate in Quantitative Research Methodologies. His core research interest is causal inference, particularly in settings where key variables of interest (e.g., outcomes or predictors) are not directly observed but are typically measured through tests, surveys, or questionnaires. These types of variables are known as latent variables or constructs that cannot be measured directly or perfectly in the same way as variables such as height, weight, or age. Machine learning and AI models do not have a measurement model to explicitly account for this type of measurement error, therefore, Amota’s current research focuses on developing and applying causal AI and machine learning methods that can improve causal inference in settings involving latent variables. He brings together ideas from psychometrics, causal inference, and machine learning to develop methods that account for measurement error while also allowing for nonlinear relationships, interactions, and other complexities in the data. Amota's dissertation in causal machine learning for latent variables has been recognized nationally through the 2026–27 National Academy of Education/Spencer Dissertation Fellowship. He is currently extending this methodological work to item response theory (IRT), developing a data-adaptive framework for estimating causal effects when variables are measured using binary or categorical test and survey items.

Under his broader interest in causal inference, Amota also focuses on the design of studies examining treatment, mediation, and moderation effects in multilevel and multisite settings. His work addresses practical questions about how many participants, clusters, or sites are needed to detect causal effects with adequate statistical power. This includes developing methods for planning studies involving clustering and mediation, as well as estimating design parameters from large-scale datasets that researchers can use to inform future experimental and quasi-experimental studies. Related to this work, he is contributing a chapter on cluster randomized trials to the Oxford Handbook of Impact Evaluation.

Amota regularly presents his research at the American Educational Research Association (AERA), Modern Modeling Methods (M3), the American Evaluation Association (AEA), the Society for Research on Educational Effectiveness (SREE), and the Association for Public Policy and Management (APPAM).

Catherine is a doctoral student in the School of Criminal Justice at the University of Cincinnati. She holds a Bachelor's degree in Psychology (2016) and a Master’s in Applied Behavioral Science with a concentration in criminal justice (2020) from Wright State University. Her research interests lie in corrections specifically focusing on offender rehabilitation, prisoner reentry, in-prison programming, and specialty courts.

Tiffany is a highly motivated and experienced educator passionate about early childhood education. She is currently a doctoral student in Educational Studies at the University of Cincinnati, where she is concentrating in Curriculum Studies and Teacher Education. Tiffany holds undergraduate degrees in Early Childhood and Inclusive Early Childhood Education and a master's degree in Curriculum & Instruction with a focus on STEM Learning. Her research interests include mathematics and science education, STEM/STEAM learning, and play-based learning.