About
Souvik Dhara is an Assistant Professor in Purdue University's Edwardson School of Industrial Engineering with a courtesy appointment in Mathematics. His research develops probabilistic frameworks and spectral algorithms for analyzing complex networks, addressing fundamental questions about hidden patterns and microscopic-to-macroscopic behavior in graph-structured data.
Key research areas include: 1) Community detection in networks using spectral methods 2) Phase transitions in random graphs 3) Large deviation theory for network properties 4) Graph limit theory applications to non-parametric statistics. His work on spectral algorithms has established optimal recovery bounds for planted substructures under censored data conditions.
Honors include the Stieltjes Prize for best mathematics PhD thesis in the Netherlands, Simons-Berkeley Fellowship, AMS-Simons Travel Grant, and multiple industry fellowships. He mentors students in random graph theory and stochastic processes, with upcoming transition to Georgia Tech as Tennenbaum Early Career Assistant Professor.
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