Charalampos (Babis) Tsourakakis, Junior Faculty Fellow, Gives 9/12 Wed@Hariri/Meet Our Fellows Talk
Wednesday, September 12, 2018, 3:00 PM – 4:30 PM
Refreshments & networking at 2:45 PM
Hariri Institute for Computing
111 Cummington Mall, Room 180
The Hariri Institute for Computing kicks off its 2018-2019 “Meet Our Fellows” series, which will showcase the Institute’s 2018 cohort of Junior Faculty Fellows.
Meet Our Fellows/Junior Faculty Fellow Presentation
Charalampos (Babis) Tsourakakis
Junior Faculty Fellow, Hariri Institute for Computing
Assistant Professor, Computer Science (CAS)
With an introduction by Abraham Matta, Professor of Computer Science.
Multifaceted Large-Scale Graph Mining
Abstract: Mining large-scale graphs is of great importance to many applications, including anomaly detection in security, community detection in social networks, and understanding the structure of the Web graph. Modern technological, social, and enterprise advancements including online, planetary-scale social networks, crowdsourcing technologies, online dating algorithms, give rise to a wealth of new graph mining problems. For example, can we use noisy crowdsourced answers to solve efficiently the entity resolution problem? Can we use the structure of a signed social network to predict if an unknown social interaction between two users will be positive or negative? Can we improve community detection algorithms, especially now that we can evaluate algorithms on ground-truth communities from online social networks? How can we recommend a set of dates between humans on a dating site that have both a large reward in expectation and a high probability of success simultaneously? How can we recommend a set of dates between humans on a dating site that have both a large reward in expectation and a high probability of success simultaneously? Babis will provide answers to these algorithmic and learning graph mining challenges, and will conclude with some future research directions.
Bio: Charalampos (Babis) Tsourakakis is an assistant professor in computer science at Boston University and a research associate at Harvard. Tsourakakis obtained his PhD in Algorithms, Combinatorics and Optimization at Carnegie Mellon under the supervision of Alan Frieze, was a postdoctoral fellow at Brown University and Harvard under the supervision of Eli Upfal and Michael Mitzenmacher respectively. Before joining Boston University, he worked as a researcher in the Google Brain team. He won best paper in IEEE Data Mining, has delivered three tutorials in the ACM SIGKDD Conference on Knowledge Discovery and Data Mining, and has designed two graph mining libraries for large-scale graph mining, one of which has been officially included in Windows Azure. His research focuses on data mining and machine learning with a strong focus on large-scale networks.