I am currently completing the accelerated MPH in Epidemiology at the Milken Institute School of Public Health at The George Washington University. My training emphasizes the evaluation of causal and associative methodologies for investigating public issues at the population level, with particular attention to how evidence is produced, interpreted, and acted upon within institutional settings.

As my program has progressed, I have begun to integrate coursework in artificial intelligence, including AI in Global Health Systems and Trustworthy AI, alongside formal epidemiologic training. This shift reflects a growing interest in how computational systems are incorporated into public health decision-making, and how issues of uncertainty, accountability, and risk emerge at the intersection of technical models and social institutions. I will conclude this phase of training with a practicum in epidemiology.

Following graduation in July 2026, I seek to continue this work through either doctoral study or a research-oriented nonprofit or think tank. My goal is to consolidate prior training in sociology, computing, and epidemiology within a structured mentorship environment, and to develop research that meaningfully connects methodological rigor with real-world institutional contexts. I am particularly interested in settings that support interdisciplinary inquiry into sociotechnical systems and emerging forms of governance around artificial intelligence.