Areas of Focus
Forty advanced graduate students and post-doctoral researchers from across the country gathered on August 5th at the H. Milton Stewart School of Industrial and Systems Engineering (ISyE) to participate in the first Foundation of Data Science Summer School hosted by Georgia Tech.
The four-day program was organized by A. Russell Chandler III Professor and Director of Georgia Tech’s Transdisciplinary Research Institute for Advancing Data Science (TRIAD) Xiaoming Huo and Harold R. and Mary Anne Nash Early Career Professor and Assistant Professor Yao Xie. Participants were introduced to a theoretical foundation of data science with a selection of application topics. The emphasis was on the foundational concepts of statistics, optimization, and signal processing, and on the applications of these techniques in developing cross-disciplinary research.
“The participating students were exposed to a set of mathematical tools that can potentially be used to derive the fundamental bounds on the performance of various techniques that have been widely adopted in data science,” explained Huo. “While there are many online and physical events (such as bootcamps and summer schools) across the nation that teach data science tools, a summer school that emphasizes the mathematical tools and foundation of data science technique is rare. Therefore, this summer school is unique.”
The program was sponsored by TRIAD and the National Science Foundation and featured talks from a wide variety of Georgia Tech faculty including Polo Chau, an associate professor in the School of Computational Science and Engineering, Mark Davenport, an associate professor in the School of Electrical and Computer Engineering, Vladimir Koltchinskii, a professor in the School of Mathematics, and Arkadi Nemirovski, John Hunter Chair and professor in ISyE, in addition to Huo and Xie. Huan Yan (Ph.D. 14), a data scientist at Wells Fargo, brought additional industry perspective to the class.
“Based on the feedback from the participants, most of them appreciate the fact that this summer school emphasizes the theoretical aspect of the data science,” said Huo. “They enjoyed the open and interactive atmosphere. Some believe that they are likely to use the ideas that they learned or developed during this summer school in their future work.”
The organizers are likely to continue organizing this type of summer school in 2020. They plan to incorporate more contents, which were recommended by this year’s participants.
TRIAD is a cross-disciplinary institute that was established in 2017 as part of the National Science Foundation’s TRIPODS (Transdisciplinary Research in Principles of Data Science) program. TRIAD unites statistics, mathematics, and theoretical computer science to further develop the foundations of data science. TRIAD brings together senior, mid-career, and junior faculty members, postdoctoral fellows, graduate and undergraduate students, all from Tech’s colleges of Computing, Engineering, and Sciences, and data science practitioners-at-large using focused working groups, national and international workshops, and organized innovation labs.