Expanding the Data Science Toolkit: Mixed Methods for Improving Causal Inference
Causalityexperts from different disciplines gathered at the Museo Galileo to discuss the field's past, present, and future, as well as hot topics in causality and causal inference in the new era of data science.Hosting the symposium at the Museo Galileo was especially fitting, as Galileo's pioneering work in experimentation, observation, and the search for underlying causal laws laid the very foundations of modern scientific reasoning.
Authors
- Noor Qaragholi (ORCID: https://orcid.org/0000-0001-5198-540X)
- Elizabeth A. Stuart (ORCID: https://orcid.org/0000-0002-9042-8611)
Institutions
- Johns Hopkins University (US)
Publication Details
- Journal
- Harvard Data Science Review
- Published
- 2025-10-31
- DOI
- https://doi.org/10.1162/99608f92.2eb6655b
- Primary Topic
- Advanced Causal Inference Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Johns Hopkins University
- Weill Cornell Medical College