Model-assisted cohort selection with bias analysis for generating large-scale cohorts from the EHR for oncology research. Benjamin Birnbaum, Nathan Nussbaum, Katharina Seidl-Rathkopf, Monica Agrawal, Melissa Estevez, Evan Estola, Joshua Haimson, Lucy He, Peter Larson, Paul Richardson. arXiv preprint, 2020.

A Machine Learning Model For Cancer Biomarker Identification In Electronic Health Records. Geetu Ambwani, Aaron Cohen, Melissa Estévez, Nisha Singh, Blythe Adamson, Nathan Nussbaum, Benjamin Birnbaum. Abstract at ISPOR 2019.

TIFTI: A Framework for Extracting Drug Intervals from Longitudinal Clinic Notes. Monica Agrawal, Griffin Adams, Nathan Nussbaum, and Benjamin Birnbaum. Machine Learning for Healthcare Workshop (ML4H) at NeurIPS 2018.

Using behavioral data to identify interviewer fabrication in surveys. Benjamin Birnbaum, Gaetano Borriello, Abraham D. Flaxman, Brian DeRenzi, and Anna R. Karlin. ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), 2013

Algorithmic approaches to detecting interviewer fabrication in surveys. Ph.D. Dissertation, University of Washington, Department of Computer Science and Engineering, 2012.

Automated quality control for mobile data collection. Benjamin Birnbaum, Brian DeRenzi, Abraham D. Flaxman, and Neal Lesh. ACM symposium on computing for development (DEV), 2012. Best paper award

Improving community health worker performance through automated SMS reminders. Brian DeRenzi, Leah Findlater, Jonathan Payne, Benjamin Birnbaum, Joachim Mangilma, Tapan Parikh, Gaetano Borriello, and Neal Lesh. Intl. conference on information and communication technologies and development (ICTD), 2012.

Distributed algorithms via gradient descent for Fisher markets. Benjamin Birnbaum, Nikhil R. Devanur, and Lin Xiao. ACM conference on electronic commerce (EC), 2011.

Convergence of local dynamics to balanced outcomes in exchange networks. Yossi Azar, Benjamin Birnbaum, L. Elisa Celis, Nikhil R. Devanur, and Yuval Peres. Symposium on foundations of computer science (FOCS), 2009.

On revenue maximization in second-price ad auctions. Yossi Azar, Benjamin Birnbaum, Anna R. Karlin, and C. Thach Nguyen. European symposium on algorithms (ESA), 2009.

Improved approximation algorithms for budgeted allocations. Yossi Azar, Benjamin Birnbaum, Anna R. Karlin, and Claire Mathieu, and C. Thach Nguyen. International colloquium on automata, languages and programming (ICALP), 2008.

On-line bipartite matching made simple. Benjamin Birnbaum and Claire Mathieu. SIGACT news, 39(1):80-87. 2008.

Competitive analysis of on-line traffic grooming in WDM rings. Karyn Benson, Benjamin Birnbaum, Esteban Molina-Estolano, and Ran Libeskind-Hadas. IEEE/ACM transactions on networks, 16(4):984-997. 2008.

An improved analysis for a Greedy remote-clique algorithm using factor-revealing LPs. Benjamin Birnbaum and Kenneth J. Goldman. International workshop on approximation algorithms for combinatorial optimization problems (APPROX 06) and Algorithmica, 55:42-59. 2009.

Achieving flexibility in direct-manipulation programming environments by relaxing the edit-time grammar. Benjamin Birnbaum and Kenneth J. Goldman. Visual languages and human-centric computing (VL/HCC), 2005.

Recent presentations

Machine Learning in Real-World Evidence. The Reagan-Udall Foundation for the FDA and Friends of Cancer Research COVID-19 Evidence Accelerator. 2020.

The Impact of Machine Learning in Healthcare Data. The Tech Trek podcast. 2020.

Artificial Intelligence for Next Generation Epidemiology and Outcomes Research. Craig S. Roberts, Benjamin Birnbaum, Wanmei Ou, Kun Huang. ISPOR 2019 Workshop.

The Role of Machine Learning & NLP in Real-World Evidence. Flatiron Health Research Summit. 2018.

Using AI to Understand Electronic Health Records in Oncology. AI Summit, New York. 2018.

Issued patents

Systems and methods for model-assisted cohort selection. Birnbaum et al. 2018.

Extracting facts from unstructured data. Shklarski et al. 2016.