Data science is making an enormous impact on science and society, but its success is uncovering pressing new challenges that stand in the way of further progress. Outcomes and decisions arising from many machine learning processes are not robust to errors and corruption in the data; data science algorithms are yielding biased and unfair outcomes, as concerns about data privacy continue to mount; and machine learning systems suited to dynamic, interactive environments are less well developed than corresponding tools for static problems. Only by an appeal to the foundations of data science can we understand and address challenges such as these.
Building on the work of three TRIPODS Phase I institutes, the new Institute for Foundations of Data Science (IFDS) brings together researchers from the Universities of Washington, Wisconsin-Madison, California-Santa Cruz, and Chicago, with the goal of tackling these critical issues. IFDS organizes its research around four core themes: complexity, robustness, closed-loop data science, and ethics and algorithms. By making concerted progress on these fundamental fronts, IFDS aims to lower several of the barriers to better understanding of data science methodology and to its improved effectiveness and wider relevance to application areas. In concert with its research agenda, IFDS engages the data science community through workshops, summer schools, and hackathons, and is committed to equity and inclusion through extensive plans for outreach to traditionally underrepresented groups.
University of Washington
University of Wisconsin
Madison
University of Chicago
University of California
Santa Cruz
Complexity
Robustness
Closed-loop
Data Science
Ethics & Algorithms
The Latest
Stephen Wright honored with a 2022 Hilldale Award
He is one of four University of Wisconsin–Madison faculty members recognized for contributions to teaching, research and service.
Rodriguez elected as a 2022 ASA Fellow
ASA Fellows are named for their outstanding contributions to statistical science, leadership, and advancement of the field.
Sebastien Roch named Fellow of Institute of Mathematical Statistics
Roch is recognized for contributions to the applications of probability theory in evolutionary biology.
PIMS-IFDS-NSF Summer School in Optimal Transport
Registration is now open at through the PIMS event webpage. Please note that the deadline to apply for funded accommodation for junior participants is Feb15.