The need to efficiently analyze large, complex data sets is a growing challenge, and one that scholars from all areas need to tackle. With this in mind, Georgia Tech launched the Transdisciplinary Research Institute for Advancing Data Science (TRIAD) on Oct. 3.
TRIAD is part of a larger National Science Foundation (NSF) project, the Transdisciplinary Research in Principles of Data Science, in which 14 institutions across 11 states collaborate on long-term big data research and training. With a $1.5 million NSF award, Georgia Tech is able to bring researchers from four of its six colleges together, representing fields such as theoretical computer science, mathematics, and statistics.
“This diversity is one of the key elements of this project,” said Stephen Cross, executive vice president for research. “New ideas come from being at the boundaries of all these fields.”
The College of Computing (CoC) has been involved in the project since the beginning. School of Computational Science and Engineering (CSE) Professor Srinivas Aluru and School of Computer Science (SCS) ADVANCE Professor of Computing Dana Randall are on TRIAD’s management team. As co-directors of the Institute for Data Engineering and Science, which submitted the NSF proposal, they already research the impact of big data but praise TRIAD’s interdisciplinary approach.
“Everyone on campus is doing something involving algorithms,” Randall said. “You can use an existing algorithm, but if you think about a problem from scratch, you can make breakthroughs.”
The community research aspect of TRIAD will be carried out by up to 40 professors and more than 250 students. The research will focus on four issues:
- advanced mathematical modeling for contemporary data;
- new inferential strategies that are both scalable and de-centralized;
- efficient optimization tools with theoretical guarantees; and
- applications in the context of large datasets from domains such as biology, design, manufacturing, logistics, and sustainability.
The first phase of TRIAD will facilitate interdisciplinary research through working groups; national and international week-long workshops featuring research presentations, tutorials, poster sessions, and panels; and organized innovation labs.
SCS Assistant Professor Jake Abernethy, School of Industrial and Systems Engineering Professor Sebastian Pokutta, and Mathematics Professor Prasad Tetali (who also holds a joint appointment in SCS) will host the first workshop on machine learning, optimization, and decision making from March 5 to 9, 2018.
Also look forward to more CoC workshops on campus throughout the spring, such as the one on algorithms and randomness led by SCS faculty Algorithms & Randomness Center Director Eric Vigoda, Professor Santosh Vempala, and Tetali from May 14 to 17, 2018.
“Our goal is to have Georgia Tech be seen as the go-to place for data science and machine learning,” said Professor Irfan Essa, associate dean for research in the College of Computing and director of the Center for Machine Learning at Georgia Tech. “This is something we’re really engaged with and invested in.”