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Danai Koutra, PhD, University of Michigan – MIDAS Seminar Series

April 21, 2017 @ 4:00 pm - 5:00 pm

Rackham Amphitheatre

Name: Danai Koutra Uniqname: dkoutra Department: EECS Photo: Joseph Xu, Michigan Engineering Communications & Marketing www.engin.umich.edu

Danai Koutra, PhD

Assistant Professor

Computer Science and Engineering

College of Engineering

University of Michigan

No Recording Available

Abstract:  Networks naturally capture a host of real-world interactions, from social interactions and email communication to brain activity. However, graphs are not always directly observed, especially in scientific domains, such as neuroscience, where monitored brain activity is often captured as time series. How can we efficiently infer networks from time series data (e.g., model the functional organization of brain activity as a network) and speed up the network construction process to scale up to millions of nodes and thousands of graphs? Further, what can be learnt about the structure of graph? How can we summarize its most important properties by taking into account the properties of other graphs in that domain (e.g., neuroscience)? In this talk I will present our recent work on scalable algorithms for inferring, summarizing and mining large collections of graph data. I will also discuss applications in various domains, including connectomics and social science.


Bio: Danai Koutra is an Assistant Professor in Computer Science and Engineering at University of Michigan, Ann Arbor. Her research interests include large-scale graph mining, graph similarity and matching, graph summarization, and anomaly detection. Danai’s research has been applied mainly to social, collaboration and web networks, as well as brain connectivity graphs. She holds one “rate-1” patent and has six (pending) patents on bipartite graph alignment. Danai won the 2016 ACM SIGKDD Dissertation Award and an honorable mention for the SCS Doctoral Dissertation Award (CMU). She has multiple papers in top data mining conferences, including 2 award-winning papers, and her work has been covered by the popular press, such as the MIT Technology Review. She earned her Ph.D. and M.S. in Computer Science from CMU in 2015 and her diploma in Electrical and Computer Engineering at the National Technical University of Athens in 2010.

For current projects, visit the GEMS Lab webpage!


For more information on MIDAS or the Seminar Series, please contact midas-contact@umich.edu. MIDAS gratefully acknowledges Northrop Grumman Corporation for its generous support of the MIDAS Seminar Series.


April 21, 2017
4:00 pm - 5:00 pm
Event Category:


Rackham Amphitheatre
915 E. Washington St.
Ann Arbor, MI 48109 United States
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