Biography

I am an Assistant Professor of Biostatistics at the Division of Biostatistics at the Department of Population Health, NYU Grossman School of Medicine. I am also a Visiting Researcher at Google, working with Ramin Zabih.

Previously, I was an Assistant Research Professor of Biostatistics at the Biostatistics Center and the Department of Biostatistics and Bioinformatics at the George Washington University School of Public Health, and a postdoctoral associate at the Cornell TRIPODS Center for Data Science and Cornell Tech mentored by Dr. Nathan Kallus and Prof. Thorsten Joachims.

My research focuses on the development and applications of statistical and data science methods for optimal decision making using real-world and experimental data.

Current:

• Axel Martin (co-advised with Ivan Diaz)
• Antonio D’Alessandro (co-advised with Samrachana Adhikari)

NYU:

• EHSCGA 2341 - Statistical Learning; PhD-level class; Fall 2022

• EHSCGA 2342 - Statistical Inference II; PhD-level class; Spring 2023; Spring 2024

• EHSCGA 2337 - Modern Causal Inference Methods; PhD-level class; Fall 2023

External to NYU:

• 03/2023 — Applied Causal Inference for Real-World Observational Studies, half-day course, Course Director, ENAR
• 06/2023 — Causal Inference in Epidemiology, week-long course, Course Director, Summer School on Modern Methods in Biostatistics and Epidemiology
• 03/2024 — Applied Causal Inference for Real-World Observational Studies, 1-day course, Course Director, Harvard Catalyst

• santam13@nyu.edu
• 180 Madison Avenue, 2nd Floor, 2-51, New York, NY 10016

When I am not reading about biostatistics and data science, I like to learn more about contemporary history. I also enjoy keeping myself active by playing sports and going to the gym. I love to play and listen to music, especially electronic and film music. During the past few years I started several electronic music projects that included production using Ableton Live. Last but not least, I love to play, cuddle and spoil my fluffy dog Mister Pom Princess ``PK” Cake.