Modern Data Modeling: Cross-Fertilization of the Two Cultures

Jianqing Fan, Cong Ma, Kaizheng Wang, Ziwei Zhu

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


The past two decades have witnessed deep cross-fertilization between the two cultures— statistics (data/generative modeling) and machine learning (algorithmic modeling), which is in stark contrast to the scene pictured in Breiman’s inspiring work. In light of this major confluence, we find it helpful to single out a few salient examples showcasing the impacts of one to the other, and the research progress out of them. We point out in the end that the current big data era especially requires joint efforts from both cultures in order to address some common challenges including decentralized data analysis, privacy, fairness, etc.

Original languageEnglish (US)
Pages (from-to)65-76
Number of pages12
JournalObservational Studies
Issue number1
StatePublished - 2021
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Statistics and Probability
  • Numerical Analysis
  • Modeling and Simulation
  • Computer Science Applications
  • Applied Mathematics


  • algorithmic modeling
  • computational thinking
  • distributed learning
  • generative modeling
  • inferential thinking


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