| Title | : | Stochastic Flow Clustering: Consolidation, Renewed Bearing and Applications to Crowdsourced Emergency Response |
| Speaker | : | Srinivasan Parthasarathy (Ohio State University, USA) |
| Details | : | Mon, 6 Aug, 2018 4:00 PM @ A M Turing Hall |
| Abstract: | : | Since its introduction in the late nineties, the idea of Markov Clustering, a graph clustering approach based on the principle of simulating stochastic flows (random walks) has seen wide use. In the first part of this talk I will review this basic idea and then describe several principled enhancements to this approach that in turn improve the quality (via regularization, and the accommodation of overlapped clustering) and speed (via sparsification, and a multi-level mechanism) of such stochastic flow algorithms so that they can be deployed on large scale problems. Results on real-world interaction networks demonstrate both the efficacy and efficiency of the approach. During the second half of the talk, I will discuss ongoing efforts on leveraging these ideas for human-in-the-loop computing for crowdsourced remote sensing and flood mapping for hurricane response. Notes: Joint work with Peter Jacobs, Albert Liang, Venu Satuluri, Yu-Keng Shih and Jiankai Sun. Bio: Srinivasan Parthasarathy is a Professor of Computer Science and Engineering and the director of the data mining research laboratory at Ohio State. His research interests span data analytics, databases and high-performance computing. He is among a handful of researchers nationwide to have won both the Department of Energy and National Science Foundation Career awards. He and his students have won multiple best paper awards or "best of" nominations from leading forums in the field including: SIAM Data Mining, ACM SIGKDD, VLDB, ISMB, WWW, ICDM, and ACM Bioinformatics. He chairs the SIAM data mining conference steering committee (elected) and serves on the action board of ACM TKDD and ACM DMKD --leading journals in the field. Since 2012 he also helped lead the creation of OSU's first-of-a-kind nationwide (US) undergraduate major in data analytics and serves as one of its founding directors |
