Big (Network) Data: Challenges and Opportunities for Data Science

Patrick J. Wolfe, Frederick L. Hovde Dean of Science and Miller Family Professor of Statistics and Computer Science, Purdue University; IEEE Signal Processing Society Data Science Distinguished Lecturer

Friday, March 22, 2019 - 3:30pm

How do we draw sound and defensible conclusions from big data? This question lies at the heart of data science. In this talk I will first describe some of the challenges and opportunities inherent in this rapidly emerging field, and then discuss the current state of the art in one area of particular relevance: big network data.  Progress in this area includes the development of new large-sample theory that helps us to view and interpret networks as statistical data objects, along with the transformation of this theory into new statistical methods to model and draw inferences from network data in the real world. The insights that result from connecting theory to practice also feed back into pure mathematics and theoretical computer science, prompting new questions at the interface of combinatorics, analysis, probability, and algorithms.

Patrick Wolfe (Data Science Lecturer)

Patrick J. Wolfe (SM) received B.S.E.E. and B.Mus. degrees from the University of Illinois at Urbana-Champaign (1998) and his Ph.D. from the University of Cambridge (2003) as U.S. National Science Foundation Graduate Research Fellow. After teaching at Cambridge from 2001–2003, he joined the faculty of Harvard University (2004) and received the Presidential Early Career Award for Scientists and Engineers from the White House (2008). In 2012, he returned to the UK to take up an Established Career Fellowship in the Mathematical Sciences at University College London (UCL), where he also served as a Royal Society Research Fellow and as founding Executive Director of UCL’s Big Data Institute. In 2017, he was appointed the Frederick L. Hovde Dean of Science at Purdue University.

Dr. Wolfe is also a trustee and non-executive director of the Alan Turing Institute, the U.K.’s National Institute for Data Science, and serves on the board of its commercial subsidiary. Previously the Institute’s Deputy Director and recently named its first honorary fellow, he played a leading role in establishing the institute and shaping its priorities through an extensive program of engagement with a diverse range of experts and stakeholders. He has provided expert advice on applications of data science to policy, societal, and commercial challenges, including to the U.S. and U.K. governments and to a range of public and private bodies—including most recently the U.K. Food Standards Agency as an inaugural member of its Science Council. Dr. Wolfe is currently Chair, IEEE SPS Big Data Special Interest Group and serves on the steering committee of the IEEE SPS Data Science Initiative, as well as Co-Chair, Data Science Section of the Institute for Mathematical Statistics.

Dr. Wolfe has received awards for his research from a number of international bodies, including the Royal Society, the Acoustical Society of America, and the IEEE. He is active in the global mathematics, statistics, and physical sciences communities, and most recently was an organizer and Simons Foundation Fellow at the Isaac Newton Institute for Mathematical Sciences 2016 semester research program on Theoretical Foundations for Statistical Network Analysis.

Seminars generally take place in 116 Old Chemistry Building on Fridays from 3:30 - 4:30 pm. For additional information contact: karen.whitesell@duke.edu or phone 919-684-8029. Sorry, but we do not have reprints available. Please feel free to contact the authors by email for follow-up information, articles, etc. Reception following seminar in 203B Old Chemistry.

Old Chemistry 116

Location Info