Foundation of Data Science (FDS) Summer School 2019
This summer school will introduce participants to a theoretical foundation of data science, with a selection of application topics. The emphasis will be on foundational concepts from statistics, optimization, and signal processing, and applications of these techniques in developing cross-disciplinary research. Topics include optimization, high-dimensional statistics, uncertainty quantifications, signal processing, and various models. The summer school is sponsored by the NSF TRIPODS Institute at the Georgia Institute of Technology. See triad.gatech.edu for more information.
The summer school will cover lodging. The participants will be responsible for their travel expenses. The application deadline is Friday, May 24, 2019, and application decisions will be announced on Friday, May 31, 2019. We expect to admit 20-30 student participants from the applications.
The intended audience for the summer school is advanced graduate students and postdoctoral researchers with a background in statistics, computer science, mathematics or related fields.
- Xiaoming Huo
ISyE, A. Russell Chandler III Professor
- Yao Xie
Harold R. and Mary Anne Nash Early Career Professor and Assistant Professor
Tentative Invited Instructors
- Arkadi S Nemirovski (Professor, Georgia Tech ISyE)
- Vladimir I Koltchinskii (Professor, Georgia Tech Math)
- Mark Davenport (Associate Professor, Georgia Tech, ECE)
- Li Deng (Citadel, Chief AI Officer)
- Workflow Status: Published
- Created By: Xiaoming Huo
- Created: 03/25/2019
- Modified By: Scott Jacobson
- Modified: 05/29/2019