Hello! I’m currently a quantitiative scientist at Flatiron Health in New York, where I work on statistical methods for EHR data to support oncology research.
I completed my PhD in the Department of Biostatistics at the University of Washington, where I worked with Ali Shojaie on causal inference and machine learning methods for analyzing network-structured data. Before starting my PhD, I graduated with a BMath from the University of Waterloo. I am proudly Canadian, and was born and raised in Mississauga, a suburb of Toronto, ON.
In my spare time, I like to read fiction, watch extreme amounts of TV, listen to podcasts, and avoid the outdoors as much as possible (sometimes I’ll go running). When time and money allow, I also love to travel, and spend an unhealthy amount of time searching for cheap flights and churning for credit card rewards.
- David Arbour, Drew Dimmery, and Arjun Sondhi (2020+). “Permutation Weighting”. Under review. [arxiv]
- Arjun Sondhi and Ali Shojaie (2020+). “Two-way network penalized regression with applications to metabolomics profiling data”. Under review.
- Jean Feng, Arjun Sondhi, Jessica Perry, and Noah Simon (2020+). “Selective prediction-set models with coverage guarantees”. Under review. [arxiv]
- Arjun Sondhi, David Arbour, and Drew Dimmery (2020). “Balanced off-policy evaluation in general action spaces”. Published in International Conference on Artificial Intelligence and Statistics (AISTATS 2020). [arxiv]
- Arjun Sondhi and Ali Shojaie (2019). “The Reduced PC-Algorithm: Improved Causal Structure Learning in Large Random Networks”. Published in Journal of Machine Learning Research. [arxiv]
- Arjun Sondhi and Kenneth M. Rice (2017). “Fast permutation tests and related methods, for association between rare variants and binary outcomes”. Published in Annals of Human Genetics. [arxiv]
- Arjun Sondhi and Ali Shojaie (2016). “Causal structure learning with reduced partial correlation thresholding”. Published in IEEE Conference on Data Science and Advanced Analytics (DSAA 2016).