Preprint

Abstract: We study a nonparametric contextual bandit problem where the expected reward functions belong to a Hölder class with …

Abstract: The increasing impact of algorithmic decisions on people’s lives compels us to scrutinize their fairness and, in …

We study the problem of learning conditional average treatment effects (CATE) from observational data with unobserved confounders. The …

Assessing the fairness of a decision making system with respect to a protected class, such as gender or race, is challenging when class …

Valid causal inference in observational studies often requires controlling for confounders. However, in practice measurements of …

Publications

Abstract: We study a nonparametric contextual bandit problem where the expected reward functions belong to a Hölder class with …

Abstract: The increasing impact of algorithmic decisions on people’s lives compels us to scrutinize their fairness and, in …

We study the problem of learning conditional average treatment effects (CATE) from observational data with unobserved confounders. The …

Assessing the fairness of a decision making system with respect to a protected class, such as gender or race, is challenging when class …

Valid causal inference in observational studies often requires controlling for confounders. However, in practice measurements of …

Teaching

I am a teaching assistant for the following courses at Cornell University:

  • ORIE 5750/CS 5785 Applied Machine Learning, 2019 FALL.
  • BTRY 6010/ILRST 6100 Statistical Methods I, 2016 FALL, 2017 FALL.
  • STSCI 5110/ILRST 5110 Statistical Methods for Social Science, 2018 Spring.

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