Dr. Eun-Young Mun
Professor, Department of Health Behavior and Health Systems
Education & Experience:
I received my BA and MA in Psychology from Yonsei University, Seoul, South Korea, and my PhD in Developmental Psychology from Michigan State University, East Lansing, MI. Prior to joining the School of Public Health faculty in January 2018, I held faculty positions at the University of Alabama at Birmingham (UAB, 2002-2006) and Rutgers, the State University of New Jersey (Rutgers, 2006-2017). I have had faculty/graduate faculty appointments in the Departments of Pediatrics, Psychology, Public Health, and Statistics, and in research centers, including the Center of Alcohol Studies at Rutgers (2006-2017).
Teaching Areas & Public Health Interests:
I have over 20 years of teaching experience at the undergraduate and graduate levels. I have taught courses in human development, adolescent and young adult health behavior, and applied statistical methods. At HSC, I have taught scientific writing courses for MS and PhD students to help produce discovery-based manuscripts for publication in peer-reviewed journals and advanced seminar courses in biostatistics for PhD students. Over my career, I have also trained many undergraduate and graduate students and postdoctoral fellows for research. Many of the previous trainees with whom I have worked have published their research in high impact peer-reviewed journals, secured research training funding (F31, L30, K01, R01 supplement) from the National Institutes of Health, and subsequently launched successful careers in research-intensive universities as faculty members or postdoc fellows (e.g., Yale Medicine, Ewha Womans University, University of Kentucky), or in technology or financial industries (e.g., Google, Amazon, American Express). Over my career as an educator, researcher, and mentor, I have made connections across various fields, which can be helpful for training and career opportunities for trainees.
Professional Activities & Awards:
I am an active member of several national organizations, including the American Public Health Association (APHA), the American Statistical Association (ASA), the Association for Psychological Science (APS), the Research Society on Alcoholism (RSA), and the Society for Prevention Research (SPR). I have also served on NIH grant review committees as a standing or ad hoc member continuously since 2010: AA-2 Study Section on Epidemiology, Prevention and Behavioral Research for the National Institute on Alcohol Abuse and Alcoholism (NIAAA); Addiction Risks and Mechanisms (ARM) Study Section for the Center for Scientific Review; NIAAA Special Emphasis Review Panels ZAA1 GG (32); NIMH Special Emphasis Review Panels, ZMH1 ERB-B (07) S and ZMH1 ERB-B (05). In addition, I have served on editorial boards for several peer-reviewed journals, reviewed manuscripts for more than 30 different journals, and served on accreditation review committees for doctoral programs in clinical psychology across the United States (US). I have an active R01 grant (R01 AA 019511), a large-scale research synthesis project that has been funded since 2010. I work with a large network of investigators and data contributors in the US. I have also provided invited lectures for grand rounds or for research colloquia at various universities in the US as well as abroad.
I have two broad research goals – One is to provide trustworthy answers in the alcohol and addiction research field, and the other is to develop and apply innovative statistical methods to address the former better. My research effort for “moving the needle” has resulted in a large-scale collaborative project titled “Project INTEGRATE” in which domain experts (intervention developers and evaluators) and statisticians come together to provide the best evidence that we can offer to major stakeholders and provide suggestions regarding how to optimize intervention for a greater impact. To do so, we have conducted a comprehensive and systematic review of the existing evidence to collect aggregate data and individual participant data from clinical trials for network and multivariate meta-analyses or one-step multilevel, integrative data analyses.
More broadly, I have long been interested in novel methods to shed new light on the development, prevention, and intervention of alcohol problems among adolescents and young adults. I have used various study designs and data modeling approaches, including structural equation modeling, mixture modeling, item response theory modeling, model-based cluster modeling, and Bayesian multilevel modeling. Recently, to complement clinical trial data with real-world data, my research team now utilizes nonparametric methods, Bayesian methods, and machine learning algorithms to better handle experimental and clinical data with small n and large p, big noisy data, and data from data repository sites in our effort to help determine “right patient, right medicine, right time.”
To access publicly available articles, https://www.ncbi.nlm.nih.gov/myncbi/eun-young.mun.2/bibliography/public/
This page was last modified on December 7, 2020