Hello! I’m currently a senior data scientist at Flatiron Health in New York, where I work with EHR data in support of oncology research and clinical care. I am broadly interested in applying statistical and machine learning methods to solve applied problems in healthcare.

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.

Publications

• Arjun Sondhi, Alexander S Rich, Siruo Wang, and Jeffrey T Leek (2023). “Postprediction Inference for Clinical Characteristics Extracted With Machine Learning on Electronic Health Records”. Published in JCO: Clinical Cancer Informatics.
• Corey M Benedum, Arjun Sondhi, Erin Fidyk, Aaron B Cohen, Sheila Nemeth, Blythe Adamson, Melissa Estévez, and Selen Bozkurt (2023). “Replication of Real-World Evidence in Oncology Using Electronic Health Record Data Extracted by Machine Learning”. Published in Cancers.
• Arjun Sondhi, Janick Weberpals, Chengsheng Jiang, Prakirthi Yerram, Michael Taylor, Meghna Samant, and Sarah T Cherng (2023). “A systematic approach towards missing lab data in electronic health records: a case study in non-small cell lung cancer and multiple myeloma”. Published in CPT: Pharmacometrics & Systems Pharmacology.
• Arjun Sondhi (2022). “Estimating survival parameters under conditionally independent left truncation”. Published in Pharmaceutical Statistics. [arxiv]
• Jean Feng, Arjun Sondhi, Jessica Perry, and Noah Simon (2021). “Selective prediction-set models with coverage guarantees”. Published in Biometrics. [arxiv]
• Arjun Sondhi, Brian Segal, Jeremy Snider, Olivier Humblet, and Margaret McCusker (2021). “Bayesian additional evidence for decision making under small sample uncertainty”. Published in BMC Medical Research Methodology.
• David Arbour, Drew Dimmery, and Arjun Sondhi (2021). “Permutation Weighting”. Published in International Conference on Machine Learning (ICML 2021). [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).