Shelley H Liu

Shelley H Liu, PhD

About Me

Dr. Shelley H. Liu is an Associate Professor (Investigator/Tenure-Track) in the Department of Population Health Science and Policy, at the Icahn School of Medicine at Mount Sinai. Dr. Liu received her PhD in Biostatistics from Harvard University, and her BA in Biological Sciences and Statistics from Northwestern University. Her research integrates psychometrics and biostatistics with applications in environmental health, child neurodevelopment, and cognitive aging research. She is the principal investigator of a R01 funded by the National Institute of Environmental Health Sciences, to develop a PFAS exposure burden calculator (R01ES035804; 2025-2030). This novel tool will enable researchers to summarize a person’s cumulative exposure to PFAS environmental toxins, allowing for cross-study harmonization, report-back of PFAS exposure burden scores to participants, and clinical biomonitoring. She is also the recipient of a National Institute of Child Health and Human Development Career Development Award (K25HD104918; 2021-2026). Through that award, she is developing psychometric methods to study how environmental toxins impact childhood executive function trajectories. She has expertise in latent variable modeling, item response theory, structural equation modeling, longitudinal data analysis, Bayesian inference, and specialized methods to study the impacts of environmental toxins and chemical mixtures on health outcomes. In addition, she collaborates as a biostatistics co-investigator on National Institutes of Health-funded grants on Alzheimer’s Disease, diabetes, health policy, environmental health, and child neurodevelopment. Dr. Liu is also committed to teaching and mentoring, and is a co-mentor on three NIH-funded K awards. She welcomes inquiries about new collaborations and inquiries from students seeking research projects.

Language
English
Position
ASSOCIATE PROFESSOR | Population Health Science and Policy
Research Topics

Alzheimer's Disease, Bioinformatics, Biomedical Informatics, Biostatistics, Cognitive Neurology, Computer Simulation, Diabetes, Environmental Health, Epidemiology, Health Services Research, Metabolomics, Obesity, Patient Centered Outcomes Research, Pediatrics, Psychiatry, Public Health, Stress

Multi-Disciplinary Training Areas

Artificial Intelligence and Emerging Technologies in Medicine [AIET]

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