There is an urgent need to develop models that can inform policy makers, as well as the general public, in responding to the COVID-19 pandemic. An interdisciplinary coalition hosted by the American Family Insurance Data Science Institute is rapidly curating information.
Are you looking for campus data and computing resources to support your research? Interested in starting new collaborations with data scientists and other researchers on campus? Looking for training in data and computing skills? The Data Science Hub's team of expert facilitators provides consultations and training.
UW-Madison offers a BA/BS in Data Science in the College of Letters and Science. Additionally, many Master's and Ph.D. programs on campus involve data science. This website is your starting point to explore majors and courses in data science at UW-Madison.
Faces of Data Science
“Like almost any new technology, data science can be used for both good and ill. Fundamental work, like the work I do, can by its nature contribute to both ends. Naturally, we hope that good purposes, like improved medical imaging and faster drug discovery, outweigh the bad!”
George B. Dantzig Professor, Sheldon Lubar Chair, and Amar and Balinder Sohi Professor of
Computer Sciences, UW-Madison
Steve Wright designs algorithms that can solve the major computational problems in data science, using mathematical tools to understand how these algorithms work. He mainly uses mathematical tools from optimization, a field that provides a set of these tools for formulating and solving problems in all areas of science, engineering, and statistics. Optimization is the basis of most algorithms used in data science.
One example of his contributions is Hogwild!, which recently won the Test of Time award from NeurIPS, the flagship conference in machine learning. Hogwild! is a version of the stochastic gradient algorithm that can perform efficiently and reliably on parallel computers without any synchronization between the different processors. (Stochastic gradient is the workhorse algorithm in data science—it is used to "train" neural networks that are the dominant technology in machine learning.) Another example is Steve’s work with coordinate descent methods, in which large optimization problems are broken down into a sequence of smaller problems.
For Steve, the chief delight of the past 15 years has been the realization that his original research area of optimization is central to data science and is front-and-center in a major scientific revolution.
Data science is an emerging field that is roughly defined as the study, development, and application of methods that reveal new insights from data, which include numbers, text, images, graphs, sounds, code, and metadata. This website provides an inclusive data science portal to guide people to relevant resources and activities at UW-Madison.
As data reshapes our world, UW–Madison brings the power of data science to every field of study. The future path of data science will be shaped by insights from all disciplines.