News & Events

Recent Publications

(2021). Fairness in Risk Assessment Instruments: Post-Processing to Achieve Counterfactual Equalized Odds. Proceedings of the 2021 Conference on Fairness, Accountability, and Transparency.

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(2020). Challenges in obtaining valid causal effect estimates with machine learning algorithms. American Journal of Epidemiology (in press).

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(2020). Counterfactual risk assessments, evaluation, and fairness. Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency. Barcelona, Spain.

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(2019). When the Oracle Misleads: Modeling the Consequences of Using Observable Rather than Potential Outcomes in Risk Assessment Instruments. NeurIPS Workshop: ‘Do the right thing’: machine learning and causal inference for improved decision making. Vancouver, Canada.

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(2019). Modeling risk and achieving algorithmic fairness using potential outcomes. AAAI/ACM Conference on Artificial Intelligence, Ethics, and Society (AIES). Honolulu, HI.

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(2018). Clustering students and inferring skill profiles with skill hierarchies. Doctoral consortium paper presented at the 11th International Conference on Educational Data Mining. Buffalo, NY.

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(2017). Filtering tweets for social unrest. Proceedings of the IEEE 11th International Conference on Semantic Computing (ICSC). San Diego, CA.

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Honors and Awards

  • 2019 Travel grant, Conference on Neural Information Processing Systems (NeurIPS).
  • 2019 Travel grant, AAAI/ACM Conference on Articial Intelligence, Ethics, and Society (AIES).
  • 2018 Best poster award: Optimized Random Partition Tree-based Kernels. Convex Optimization Mini-Conference, Carnegie Mellon, Pittsburgh, PA. Co-authors: Benjamin LeRoy, Niccolò Dalmasso.
  • 2017 Winner of the Fall 2017 Citadel Data Open at Carnegie Mellon. (550 student applications, 125 selected to compete; $20,000 prize). Teammates: Niccolò Dalmasso, Kwangho Kim, Chirag Nagpal.
  • 2017 Best short talk: "Subspace Clustering," Statistical Machine Learning Mini-Conference, Carnegie Mellon, Pittsburgh, PA.