Summer 2018 Causal Inference Workshops

Duke University, Durham NC

Investigators

Abstract

This award provides partial support for new researchers to attend two conferences on causal inference in summer 2018: The Atlantic Causal Inference Conference (ACIC) held in Pittsburgh, PA on May 22-23, 2018 and the Causal Workshop at the Conference on Uncertainty in Artificial Intelligence (UAI) held in Monterey, CA on August 6-10, 2018. Both conferences serve as flagship gatherings of leaders in reasoning about causes of observed effects. In recent years, causal inference has seen important advances, especially through a dramatic expansion in its theoretical and practical domains. Machine learning methods have focused on ultra-high-dimensional models and scalable stochastic algorithms, whereas more classical causal inference has been guiding policy in complex domains involving economics, social and health sciences, and business. Through such advances, a powerful cross-pollination has emerged as a new set of methodologies promising to deliver more robust data analysis than each field could individually. The primary purpose of the two conferences is to advance the study of causal inference and to bridge gaps between different communities within causal inference, by promoting interaction and networking among new researchers. At both conferences, the supported participants will present their research via invited and contributed talks or via poster presentations. Since the conferences draw on causal inference communities in statistics, biostatistics, computer science, and other disciplines, these conferences present a great opportunity for new researchers to see the breadth of opportunities for research and collaboration in this area. More information is available at the conference web sites: ACIC: https://www.cmu.edu/acic2018/ UAI: https://sites.google.com/view/causaluai2018 This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.