Associate Professor of Satistics Babak Shahbaba, together with co-principal investigators Hongkai Zhao and Jeffrey Streets from UCI’s Department of Mathematics, have received $250,000 from the National Science Foundation (NSF) for their project, “Theory and practice for exploiting the underlying structure of probability models in big data analysis.” According to Shahbaba, the project aims to “develop a theoretical framework to study underlying structures of statistical models and use this framework in practice to design efficient and scalable computational methods and algorithms for Bayesian inference.”

The project will attempt to catch data analysis up to the current “data deluge” generated by increasingly powerful scientific experiments, routine use of digital sensors and intensive computer simulations. Current data analysis tools lack the theoretical foundation as well as computational complexity and scalability to find effective and computationally feasible methods for processing and analyzing very large datasets, the research team notes. Ultimately, Shahbaba and the research team will develop novel techniques to be applied to real computationally intensive problems from the biological sciences.

“Due to its interdisciplinary nature, this research is expected to contribute to several fields, including statistics, machine learning, applied mathematics, and data-intensive computing,” the research team notes.

The NSF award comes from its Division of Mathematical Sciences (DMS), which supports research in mathematics and statistics, training through research involvement of the next generation of mathematical scientists, conferences and workshops, and a portfolio of national mathematical sciences research institutes.