I am a fifth year Mathematics PhD student at Purdue University. My advisor at is Dr. David F. Gleich of Purdue's computer science department..
My research is in matrix computations and graph analysis. In particular I have done a lot of work with algorithms for graph clustering.
I've been working as a research assistant in the comptuer science department at Purdue University for my advisor David Gleich since Spring 2015. My research lies at the intersection of graph theory and numerical optimization. Primarily I focus on optimizing difficult graph algorithms by analyzing properties of the input graphs and by exploiting the special structure present in the matrices associated with graphs, such as the adjacency, incidence, and Laplacian matrices. The goal is to find efficient solutions to problems that in general might be NP-hard but are not intractable for special cases. Another focus is finding fast and accurate approximations when quick exact algorithms to solve hard problems are not available. Recently I've worked a lot of graph clustering algorithms, including methods for flow-based local graph clustering and clustering in low-rank signed graphs using correlation clustering.
During summer 2016 I was funded as an East Asia and Pacific Summer Institute Fellow. For this program I traveled to the University of Melbourne during the months of June and July 2016 to work with Associate Professor Anthony Wirth on a project involving correlation clustering on low-rank matrices. The results of our summer work and subsequent follow-up work appeared in this year's World Wide Web Conference.
I am not teaching this semester, but here is a list of my previous teaching experience.
In Fall of 2015 I received the Purdue Mathematics Department Excellence in Teaching Award:
Purdue Math Department Excellence in Teaching Award 2015
Since Fall of 2016 I have been the organizer for the Purdue University Numerical Linear Algebra Group, a seminar series on matrix computations and network analysis. All PUNLAG talks are recorded and uploaded to YouTube. You can subscribe to the Purdue Numerical Linear Algebra YouTube channel at PurdueNLA.