Noah's research integrates two interconnected lines of quantitative research: evaluating the strength of causal inference across the pathway from publication to popular consumption, and global HIV/AIDS measurement and evaluation. His methodological roots in health economics and econometrics were developed largely during his doctoral years at the Harvard TH Chan School of Public Health, with additional interdisciplinary studies and collaboration in epidemiology during his prior postdoctoral fellowship at the University of North Carolina. Noah's meta science work bridges gaps in the methodological approaches between econometrics and those more typically found in epidemiology. The centerpiece of his causal inference work is developing systems and methods of large-scale, sustainable, and interdisciplinary scientific review for causal inference, designed for interventions and institutional review at all levels of the science generation, distribution, and consumption process. Noah's HIV work is similarly cross-cutting, including testing methods to improve the scientific rigor of methods for evaluating health systems performance and piloting and testing survey data collection methods.