News & Events

Recent Publications

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

Preprint

(2020). Achieving Counterfactual Fairness in Risk Assessment Instruments. Talk at the CMU Symposium on AI and Social Good. Pittsburgh, PA.

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

Preprint PDF

(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.

Preprint

(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.

Preprint PDF

(2015). Using structural topic modeling to detect events and cluster Twitter users in the Ukrainian crisis. 17th International Conference on Human-Computer Interaction. Los Angeles, 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.