Data Science Institute

BIGDATA: Analytical Approaches to Massive Data Analysis

Research Project

The goal of this project is to design and test mathematically well-founded algorithmic and statistical techniques for analyzing large-scale, heterogeneous and noisy data. 

BigdataThe proposed research is transformative in its emphasis on rigorous, analytical evaluation of algorithms' performance and statistical measures of output uncertainty, in contrast to the primarily heuristic approaches currently used in data mining and machine learning. Any progress in that direction will have a significant contribution to the reliability and scientific impact of the massive data analysis. 

Research Lead

Eli UpfalProfessor of Computer Science, Brown University

Funding Sources

NSF, NIH, corporation gifts