Community Detection in Preferential Attachment Graphs by Suryanarayana Sankagiri

Location: Auditorium, ECE MP Building

Name of the speaker: Suryanarayana Sankagiri.

Title of the talk: Community Detection in Preferential Attachment Graphs.

Date and time: Wednesday, 19 June 2019 at 4 pm (tea/coffee at 3:45 pm).

Venue: MP Auditorium, ECE Department.


Can the structure of a network reveal how it is formed? Community  detection, or graph clustering, is an important field in modern data  science that studies how to extract useful information from the structure of social networks, citation networks, etc. In recent years, the field has  seen important theoretical breakthroughs via the development of algorithms  with provable performance guarantees on random graphs. This talk develops  on this theme with an exposition of a hitherto unexplored random graph  model that better represents real world networks.

A preliminary version of this work was presented at International Symposium on Information Theory, 2018. An extended version can be found at


Suryanarayana Sankagiri is a Ph.D. candidate in Electrical and Computer Engineering at the University of Illinois, Urbana Champaign, working under the supervision of Dr. Bruce Hajek. He obtained his B. Tech from IIT Bombay in 2016, and M.S. from the University of Illinois in 2018. His research interests lie primarily in the modelling and analysis of engineering systems using random processes. His current focus is on modelling blockchain systems. Beyond research, he enjoys teaching as well as outdoor activities like running, biking and bird watching


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