[Colloq] REMINDER: NOW in 366 WVH Title: Mining Tools for Large-Scale Networks | Babis Tsourakakis, Harvard University | 1/27/16 366WVH 2pm-3pm

[Walker, Lashauna]

Title: Mining Tools for Large-Scale Networks
Speaker: Babis Tsourakakis
Date/Time: 1/27/16  2-3pm (NOW)
Location: 366 WVH



Title: Mining Tools for Large-Scale Networks



Abstract:

Finding large near-cliques in massive networks is a notoriously hard problem of great importance to many applications, including anomaly detection in security, community detection in social networks, and mining the Web graph. How can we exploit idiosyncrasies of real-world networks in order to solve this NP-hard problem efficiently? Can we find dense subgraphs in graph streams with a single pass over the stream?  Can we design near real time algorithms  for time-evolving networks? In this talk I will answer these questions in the affirmative. I will present state-of-the-art exact and approximation algorithms for extraction of large near-cliques from large-scale networks, the k-clique densest subgraph problem, which run in a few seconds on a typical laptop.  I will present graph mining applications, including anomaly detection in citation networks, planning a successful cocktail party, and engineering applications on Tera-scale networks. I will conclude my talk with some interesting research directions.

Bio:

Dr. Charalampos Tsourakakis is currently a CRCS Postdoctoral Fellow in the School of Engineering and Applied Sciences (SEAS) at Harvard University. He received his Ph.D. from the Algorithms, Combinatorics and Optimization (ACO) program at Carnegie Mellon University (CMU). He also holds a Master of Science from the Machine Learning Department at CMU. He did his undergraduate studies in the School of Electrical and Computer Engineering (ECE) at the National Technical University of Athens (NTUA). He is the recipient of a best paper award in IEEE Data Mining, and has designed two graph mining libraries for tera-scale graphs. The former has been officially included in Windows Azure, while the latter was a research highlight of Microsoft Research. His main research interest lies in designing scalable and data-aware algorithms for massive networks that recover hidden structure and solve complex data-driven problems.




Thank You.

LaShauna Walker
Events and Administrative Specialist
College of Computer and Information Science
Northeastern University
617-373-2763
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