Mission

As data continues to accumulate at an ever increasing rate, so does the need for powerful and novel methods to extract information from data, in a form that is useful to individuals, society, researchers, and commerce. Research into the fundamentals of data science brings people with expertise in mathematics, statistics, and theoretical computer science together in a concerted transdiciplinary effort to explore new approaches to the formulation and solution of problems in data analysis. A previous generation of researchers at UW-Madison made foundational contributions to data science, in such areas as kernel learning, splines, and experimental design. The current generation of faculty is carrying forward this tradition. During the past decade, researchers across campus have done important work in diverse aspects of fundamental data science, as well as in applications to numerous areas of domain science, engineering, and medicine. This group forms the core of the Institute for Foundations of Data Science (IFDS) at UW-Madison. Building on previous work, and pursuing new goals sparked at the interfaces of mathematics, statistics, and theoretical computer science, IFDS aims to produce excellent research and to epitomize the possibilities of collaborative approach to investigating fundamental issues in data science.

News

IFDS Supporting Five Research Assistants in Fall 2018
IFDS Supporting Five Research Assistants in Fall 2018
Each are advised by two IFDS faculty and collaborate across departments.
Read More
Improved methods for studying hard-to-reach populations published in PNAS
Improved methods for studying hard-to-reach populations published in PNAS
Respondent-driven sampling is a popular network-based approach to sample hard-to-reach populations, where participants refer contacts into the sample through a coupon system. It has been...
Read More
Using Data Science to Find the Next El Nino
Using Data Science to Find the Next El Nino
A new approach to climate data analysis hopes to improve regional forecasts.
Read More
Roch wins Best Paper Award at RECOMB
Roch wins Best Paper Award at RECOMB
IFDS member Sebastien Roch and former mathematics Ph.D. student Kun-Chieh (Jason) Wang won Best Paper Award at the prestigious 22nd Annual International Conference on Research...
Read More
IFDS Supporting Four Research Assistants in Spring 2018
IFDS Supporting Four Research Assistants in Spring 2018
The funding uses NSF grant monies under the TRIPODS and Convergence Programs.
Read More
Nowak Becomes Section Editor of New SIAM Journal on the Mathematics of Data Science
Nowak Becomes Section Editor of New SIAM Journal on the Mathematics of Data Science
The new journal will begin to take author submissions in Spring 2018.
Read More