The Future of Causal Inference

Nandita Mitra, Jason Roy, Dylan Small

Research output: Contribution to journalReview articlepeer-review

1 Scopus citations


The past several decades have seen exponential growth in causal inference approaches and their applications. In this commentary, we provide our top-10 list of emerging and exciting areas of research in causal inference. These include methods for high-dimensional data and precision medicine, causal machine learning, causal discovery, and others. These methods are not meant to be an exhaustive list; instead, we hope that this list will serve as a springboard for stimulating the development of new research.

Original languageEnglish (US)
Pages (from-to)1671-1676
Number of pages6
JournalAmerican journal of epidemiology
Issue number10
StatePublished - Oct 1 2022
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Medicine(all)


  • algorithms
  • causal discovery
  • causal machine learning
  • distributed learning
  • high-dimensional data
  • interference
  • transportability


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