Robert J. Brunner

Photo of Robert J. Brunner

Professor

PhD, Astrophysics, The Johns Hopkins University

302 LIS
(217) 244-6099
bigdog [at] illinois.edu
http://lcdm.illinois.edu/

Curriculum Vitae   

Research Focus

The development of data science, the application of machine learning, algorithmic optimization, statistical uncertainty and its incorporation in machine learning, data management, effective visualization, and data storytelling.


Other Professional Appointments

Professor, Department of Accountancy
Director, University of Illinois-Deloitte Foundation, Center for Business Analytics
Data Science Expert in Residence, Research Park, University of Illinois
Affiliate Faculty, Departments of Astronomy, Computer Science, Electrical and Computer Engineering, Informatics, Physics, and Statistics
Faculty Affiliate, NCSA
Faculty Affiliate, Beckman Institute
Faculty Affiliate, Computational Science & Engineering

Biography

Robert J. Brunner is a professor in the School of Information Sciences and in the Department of Accountancy in the College of Business. He has affiliate appointments in the Astronomy, Computer Science, Electrical and Computer Engineering, Informatics, Physics, and Statistics Departments; at the Beckman Institute, in the Computational Science and Engineering program; and at the National Center for Supercomputing Applications. He is also the Data Science Expert in Residence at the Research Park at the University of Illinois.

His primary research goal focuses on the application of statistical and machine learning to a variety of real-world problems, and in making these efforts easier, faster, and more precise. This work spans fundamental algorithm design to more effectively incorporate uncertainty to optimization using novel computational technologies. More generally, Brunner helps lead efforts to promote data science across campus and to encourage effective data management, analysis, and visualization techniques.

Brunner earned his PhD in astrophysics at the Johns Hopkins University working under Alex Szalay on the development of the science archive for the Sloan Digital Sky Survey. His PhD thesis helped develop the statistical approach to quantifying galaxy evolution, where large data are used to place constraints on the original and evolution of the Universe. He subsequently spent five years as a postdoctoral scholar at the California Institute of Technology working under S. George Djorgovsi and Tom Prince as the project scientist for the Digital Sky project. 


TEACHING THIS SEMESTER

Foundations of Data Science (IS490RB)

In the News

Related Topics

Archives and Preservation, Data Analytics, Information Retrieval, Social Media