♦ Causal inference

• Life after bootstrap: Residual randomization inference in regression models
  (early draft,  pdf)
• Randomization tests under endogeneous and staggered adoption of treatment
  with Shaikh, A.
• Randomization tests for peer effects in group formation experiments
  with Basse, G.; Feller A.; Ding, P. (submitted,    arxiv pdf)
• On clustering similarity with application to causal inference with the propensity score
  with Volfovsky, A.
• Propensity score methodology in the presence of network entanglement between treatments
  with Volfovsky, A.; Airoldi, EM. (   arxiv pdf)
• Dynamical systems theory for causal inference with application to synthetic controls
  with Ding, Yi. (submitted,   arxiv pdf)

♦ Statistical machine learning/stochastic gradients

• Stable Robbins-Monro approximations through stochastic proximal updates
  with Horel, T.; Airoldi, EM. (submitted,   arxiv pdf, Winner of IBM 2018 award)

• Statistical inference and testing at scale with stochastic gradient-based estimators
  with Chee, J.
• Estimation of large-scale dynamic discrete choice models
  with Junhyung Kim, L.; Misra, S.

♦ Mechanism design/game theory

• Screening with tournaments
  with Parkes, DC. (  pdf)