University of Arkansas Spring Lecture Series in the Mathematical Sciences 2019 and 2020

University Of Arkansas, Fayetteville AR

Investigators

Abstract

The University of Arkansas Spring Lecture Series 2019 and 2020 will be held in Fayetteville, AR, on April 18-20, 2019 and April 16-18, 2020, on the topics of "Bayesian Analysis for Multivariate Dynamic Systems" and "Discrete Random Structures and Prediction in Bayesian Nonparametrics," respectively. The common theme of the two Lecture Series is how to harness the power of data using complex models within the flexible paradigm of Bayesian statistical inference. In each Lecture Series, a prominent researcher in the field will give five lectures on the topic of the conference, starting with an introductory one and reaching the boundaries of current research. Additionally, ten leading figures in the area covered by the conference will give one-hour research presentations, and there will be sessions devoted to contributed talks and poster presentations. Graduate students, recent PhDs, and new researchers are supported by this award. To facilitate the transition of graduate students to the advanced research topics that will be treated in the lectures, there will be an introductory workshop, specifically aimed at them, in the afternoon of the day before the conference begins. The 2019 conference will focus on Bayesian approaches to modeling and analysis of high-dimensional multivariate time series with a broad purview over problems of statistical analysis, structure assessment, monitoring and forecasting. Emphasis will be given on discussion of recent advances in state-space models anchored on instantiations of the decouple/recouple concept and its implied strategies that provide a powerful platform for scaling coherent statistical analysis to increasingly complex dynamic systems. State-of-the-art Bayesian modeling approaches based on this concept, as well as their broad range of applications in many different areas including financial and commercial forecasting, socio-economic, engineering and natural sciences will be covered in the lectures. The 2020 conference will give an overview of recent developments in Bayesian nonparametrics, specifically focusing on discrete random structures that are key tools for many modern inferential goals, such as topic modeling, change-point analyses or meta-analysis. Special attention will be given to the most promising research directions such as partial exchangeability and dependent nonparametric priors, spanning state-of-the-art tools in this area. The attendees will benefit from ample opportunities to forge and foster collaborations and exchange of ideas as well as exposure to open research problems in methodological and cross-disciplinary domains. More details on these conferences are available at https://fulbright.uark.edu/departments/math/research/spring-lecture-series/index.php 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.