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Email: gp77@nyu.edu
Phone: 734-645-3173
Education
- Master of Science in Applied Statistics, New York University, New York, 2020
- Master of Public Health in Health Behavior and Health Education, University of Michigan, Ann Arbor, 2018
- Bachelor of Arts in Psychology, University of Wisconsin, Madison, 2016
Professional Experience
Visiting Assistant Professor
New York University, NYU | 2023 - Present
Director of Research and Data Analysis
New York University PRIISM center, NYU | 2021 - 2023
Lead development of thinkCausal a causal inference application for learning causal inference and conducting causal inference analyses.
Developed and ran simulation studies related to Bayesian Additive Regression Trees (BART), multi‑level models and machine learning.
Behavioral Science Research Fellow
Academic Innovation | University of Michigan 2017-2018
Collaborated with Physics faculty to run a block randomized trial on a value affirmation intervention comparing in‑person implementation against a digital implementation of the intervention.
Wrote content for personalized communication interventions to increase college student motivation, performance and persistence.
Research Assistant
Harackiewicz Research Lab | University of Wisconsin 2014-2016
Coded and entered data for a field evaluation of brief educational interventions to increase STEM persistence among first generation and under‑represented college students.
Assisted with data collection and analysis for randomized studies of education interventions aimed at increasing retention rate among community college students across the state of Wisconsin
Research Assistant
Niedenthal Emotions Lab | University of Wisconsin 2015-2016
Wrote IRB applications, assisted in the development of psychometric measures, oversaw behavioral experiments.
Conducted literature reviews about affect and decision making, appraisal theory of emotions and functional accounts
Skills
- Programming Languages:
- Expert in R, R Shiny
- Proficient with STAN
- Proficient in parallel computing techniques and cluster management, enabling efficient and scalable data processing.
- R package development: I have authored 4 R package:
thinkCausal
,nyuCausal
,plotBart
andshinyQuiz
.
Publications
Hill, J., Perrett, G., & Dorie, V. (2023). Machine Learning for Causal Inference. In Handbook of Matching and Weighting Adjustments for Causal Inference (pp. 415-444). Chapman and Hall/CRC.
Dorie, V., Perrett, G., Hill, J. L., & Goodrich, B. (2022). Stan and BART for Causal Inference: Estimating Heterogeneous Treatment Effects Using the Power of Stan and the Flexibility of Machine Learning. Entropy, 24(12), 1782.
Dowell, N. M., McKay, T. A., & Perrett, G. (2021). It’s not that you said it, it’s how you said it: Exploring the linguistic mechanisms underlying values affirmation interventions at scale. AERA Open, 7, 23328584211011611.
Awards
2021 ASH Leadership Award, Awarded in recognition of the highest standard of leadership through initiative, commitment to the improvement of programs or activities, and service to the Department or School.
2016 Brian Hendricks Scholarship, Awarded in recognition of outstanding undergraduate research contribution. Given to an undergraduate RA with exemplary contribution to a psychology research lab.
2016 Athletic Board Scholar, Awarded to the varsity letter winner with the highest GPA
2015 Athletic Board Scholar, Awarded to the varsity letter winner with the highest GPA