Emerging Challenges for Statistics and Data Sciences: Complex Data with Missingness, Measurement Errors, and High Dimensionality (22w5010)

Organizers

(North Carolina State University)

David Haziza (University of Ottawa)

(University of California, Berkeley)

Chenyin Gao (North Carolina State University)

Grace Yi (University of Western Ontario)

Description

The Banff International Research Station will host the "Emerging Challenges for Statistics and Data Sciences: Complex Data with Missingness, Measurement Errors, and High Dimensionality" workshop at the UBC Okanagan campus in Kelowna, B.C., from May 22 - 27, 2022.



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Statistics and newly emerging data science are central pillars to quantitative research in social and biomedical sciences. The era of big data has revolutionized statistics with massive, heterogeneous and complex-featured data sources. It is critical and timely to bring statisticians, computer scientists, and practitioners together to share current research advances in handling novel data analytical challenges including missingness, measurement errors, and high dimensionality. This workshop will help bring researchers together to take a significant step forward in using big data to answer important scientific questions.


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. BIRS 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).