Recent Developments on Mathematical/Statistical Approaches in Data Science

University Of Texas At Dallas, Richardson TX

Investigators

Abstract

A workshop on Recent Developments on Mathematical/Statistical Approaches in Data Science will be held at the University of Texas, Dallas, in the Spring of 2019. The workshop will bring together researchers from different disciplines including computational and applied mathematics, statistics, computer science, and engineering to report on cutting-edge methodologies and state-of-the-art computational algorithms in data science. The workshop will provide an opportunity to all the participants to submit their related works to a special issue in the journal of Inverse Problem and Imaging (IPI). The funding provided will be primarily allocated in support of junior researchers such as graduate students, post-docs, and entry-level faculty members, specifically to under-represented minorities and women in the STEM. The organizers will coordinate invited speakers to serve as mentors to junior researchers during the poster session and the career luncheon. The organizers also invite speakers from different countries to promote international collaborations. Due to the blooming of 'big data' and an emerging field of data science, there is a need to bring together researchers from different disciplines to keep up with recent developments. The objectives of this workshop are (1) to facilitate discussions and foster collaborations among the participants with different backgrounds and expertise; (2) to attract new researchers to the field of data science and to offer mentoring service to junior participants in this field; and (3) to bridge the gap between the theoretical development in academia and practical applications in industry. The proposed workshop will be multidisciplinary with topics ranging from scientific computing and statistics to various applications in data science. As a result, this workshop will strengthen the relationship between mathematicians and other scientists/engineers who are interested in data science. In addition, the workshop will advance the development of computational methods, statistical theories, and tools for big data analysis. Furthermore, the workshop will build close connections between academia and industry to establish and facilitate research collaborations in a variety of data-driven applications. 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.