Research Research Projects

BIGDATA: Analytical Approaches to Massive Data Computation with Applications to Genomics

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 such as those assembled by genetic sequencing. The 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.

Research Leads: 

Eli Upfal
VISIT project website

Funding Sources: 

NSF, NIH, corporation gifts