Causal Inference with Big Data (20w5210)

Organizers

(University of California, Berkeley)

(Stanford University)

(Eidgenössische Technische Hochschule Zürich)

Fabrizia Mealli (University of Florence)

Description

The Banff International Research Station will host the "Causal Inference with Big Data" workshop in Banff from August 16 to August 21, 2020.


Causal inference is a central pillar of many scientific disciplines. Motivated by applications in different scientific fields, there has been tremendous progress in causal inference in the last twenty years. At the same time, the era of big data has presented the field with massive, heterogeneous and complex data sets, posing further challenges. It is therefore crucial and timely to bring together the researchers from both ends, in order to share recent advances, to identify pressing problems, to spark productive collaborations, and to ultimately advance the state of the art by developing new theory and methods for causal inference with big data.


The Banff International Research Station for Mathematical Innovation and Discovery (BIRS) is a collaborative Canada-US-Mexico venture that provides an environment for creative interaction as well as the exchange of ideas, knowledge, and methods within the Mathematical Sciences, with related disciplines and with industry. The research station is located at The Banff Centre in Alberta and is supported by Canada's Natural Science and Engineering Research Council (NSERC), the U.S. National Science Foundation (NSF), Alberta's Advanced Education and Technology, and Mexico's Consejo Nacional de Ciencia y Tecnología (CONACYT).