AUTOBIOGRAHPICAL SKETCH
I completed my undergraduate studies at the State University of New York at Brockport, where I majored in psychology and philosophy. For my senior year, I studied abroad at the University of Oxford, focusing tutorials on cognitive neuroscience and the history of modern philosophy. After obtaining my B.S., I began work as a research assistant at the University of Rochester. As a research assistant, I worked on a study investigating the impact of parental conflict and at-risk environments on preschool children’s cognitive and emotional development.
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I completed a doctoral degree at the University of Texas, co-advised by Dr. Elliot Tucker-Drob and Dr. K. Paige Harden. During my training, I developed expertise in psychometrics, behavioral genetics, and structural equation modeling and became a core member of the Texas Twin Project. After obtaining my Ph.D., I began a post-doctoral appointment at the University of Minnesota, working with Dr. Robert Krueger and Dr. Colin DeYoung. During this time, I also worked as a statistical consultant for the Center for Practice Transformation and taught research methods and statistics at Augsburg University. After my postdoctoral position, I began working at Stony Brook University in the Department of Family, Population, and Preventive Medicine.
Recently, I have been developing statistical models of cumulative stress and social advantage and working with the World Trade Center Health Program to coordinate a U01 study of cognitive impairment in members of the FDNY who responded to the 9/11 attacks. I've also been conducting long-term trajectory studies of psychiatric symptoms, including PTSD, depression, and psychosis, using genetic data to conduct polygenic risk score analyses and Mendelian randomization. In summary, I strive to avoid intellectual and empirical pigeonholes by integrating methods across fields to study mental health and well-being throughout the lifespan.
RESEARCH INTERESTS
Individual Differences
(e.g., psychopathology, cognitive impairment, acute and chronic stressors, social advantage)
Applied Statistics
(e.g. longitudinal data analysis, structural equation modeling, item response theory, machine learning)
Quantitative Genetics
(e.g. twin and family studies, Mendelian randomization, polygenic risk scores)