The Department of Statistics, Actuarial and Data Sciences is pleased to announce that Taps Maiti from Michigan State University will be the third of the 2022-2023 Data Science Speaker Series.
Title: Big Data: A Perspective from Statistical Foundational of Data Science
Speaker: Taps Maiti, Michigan State University Foundation Professor in the Department of Statistics and Probability
Time and Date: 11:00 am – Noon, Friday, February 10, 2023
Location: Pearce Hall 138 or by WebEx at https://cmich.webex.com/meet/famoy1kf
Abstract: The rapid development of information technology makes it possible to collect massive amounts of multidimensional, multimodal data with high frequency in diverse fields of science and engineering. New statistical and machine learning methods have been developing continuously to address the challenges arising out of these complex systems. For example, we consider a large neuroimaging classification problem with a complex spatiotemporal structure. Numerous machine-learning techniques were found helpful in analyzing such complex and big data. However, their statistical and computational foundations are not well understood. This talk will discuss several recently developed learning procedures and their computational, theoretical, and practical challenges.
BIO: Professor Tapabrata (Taps) Maiti is a Michigan State University (MSU) Foundation Professor in the Department of Statistics and Probability. Prof. Maiti has been recognized as a Fellow of the American Statistical Association (ASA), a Fellow of the Institute of Mathematical Statistics (IMS) and a Fellow of the American Association for the Advancement of Science (AAAS), an honor from the world's largest scientific body. Prof. Maiti served on the editorial board for many prestigious journals, such as the Journal of American Statistical Association (JASA), Computational Statistics and Data Analysis, Sankhya, etc. Currently, Maiti is an Area Editor for the journal of Statistical Modeling and Data Mining published by ASA as well as an Associate Editor for JASA Theory & Methods.
Posted by Carl Lee, Professor, Dept of Statistics, Actuarial & Data Sciences, Central Michigan University
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Carl Lee
Central Michigan University
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