• Four Lectures on Causality

    On May 10 and 11, Jonas Peters (University of Copenhagen) gave four lectures on causality. Slides and videos are available.
  • Causal inference and applications to learning gene regulatory networks

    Causal inference: Geometry of conditional independence structures for 3-node directed Gaussian graphical models.
  • Combinatorial learning with set functions

    Learning problems that involve combinatorial objects are ubiquitous - they include the prediction of graphs, assignments, rankings, trees, groups of discrete labels or preferred sets of a user; the expression of prior structural knowledge for regularization, the identification of sets of important variables, or inference in discrete probabilistic models.

The Statistics and Data Science Center is an MIT-wide focal point for advancing research and education programs related to statistics and data science. The Center was created in 2015 with the goal of formalizing and consolidating efforts in statistics at MIT. The Center’s academic mission is to host and develop new academic programs, from a minor to a PhD in statistics and data science.



Photo of Esther Duflo
MIT News | July 06, 2017

Study: Preschoolers learn from math games — to a point

A study co-authored by Professor Esther Duflo finds games for pre-schoolers can improve conceptual math skills, however, the gains may not carry ...

MIT News | June 29, 2017

Investigating the trap of unemployment

PhD student Aicha Ben Dhia studies France’s labor market from the perspective of local job-seekers.

MIT News | June 08, 2017

QS ranks MIT the world’s No. 1 university for 2017-18

Ranked at the top for the sixth straight year, the Institute also places first in 12 of 46 disciplines.