"Evaluating Digital Agriculture Recommendations with Causal Inference". It was accepted and presented in the special track on Artificial Intelligence for Social Impact, AAAI-23
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Updated
Sep 28, 2023 - Jupyter Notebook
"Evaluating Digital Agriculture Recommendations with Causal Inference". It was accepted and presented in the special track on Artificial Intelligence for Social Impact, AAAI-23
A Python package to access, download, view, and manipulate Cassini RADAR images in one place
Python Request Engine for Virtual Interferometric Survey
Repo for the paper "Survey calibration for causal inference: a simple method to balance covariate distributions”
This repository provides the workshop materials for latent variable models applied to data on wartime sexual violence. This workshop was previously taught at Ashoka University (2018) and Michigan State University (2019).
BIVREST — a group verification protocol for role-based behavior. "Believe/Don't Believe" voting with structured logging of actions and group decisions. A data collection method for behavioral research.
Reproduce results from the paper "Development, validation and clinical usefulness of a prognostic model for relapse in relapsing-remitting multiple sclerosis. K. Chalkou et. al. Diagn Progn Res . 2021 Oct 27;5(1):17. doi: 10.1186/s41512-021-00106-6."
Matching Methods for Time-Varying Observational Studies, in R
This repository provides the Online Appendix, replication data and materials for Krüger & Nordås, A latent variable approach to measuring wartime sexual violence, in Journal of Peace Research
Propensity scores in complex surveys
App for NWPA
Casual relationship between health insurance coverage and BMI.
Advanced Observational Astronomy, Spring 2024
Processing and analysing data gathered by mammal watching.
Inclusion-Driven Learning of Bayesian Networks
SAS and R Assignments completed at Undergraduate Applied Statistics Program
Comparative simulation study of TMLE and C-TMLE estimators for causal inference in high-dimensional observational data · R
A two-day NCRM course on causal analysis and machine learning provided in June 2021.
Creates mesopause temperature maps (not fully calibrated) from the UNIS Allsky Airglow Camera
A data analysis on the STAR observational data
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