I am a sixth year Mathematics PhD student at Purdue University. My advisor is Professor David F. Gleich of Purdue's computer science department.
My research interests lie in network analysis, optimization, and machine learning. In particular I've done a lot of work recently on algorithms for graph clustering.
I will be graduating after this year and am actively looking for academic positions starting in Fall 2019.
I've been working as a research assistant in the computer science department at Purdue University for my advisor David Gleich since Spring 2015. My research focuses on how to develop better algorithms with rigorous guarantees (in terms of runtime or approximation) for commonly-studied problems in data science and network analysis, typically by exploiting special features in the underlying data and considering specific structural properties often exhibited by real-world networks. To date, much of my research has focused on clustering in graphs, which includes the study of correlation clustering for partitioning signed graphs, using flow-based methods for localized community detection, and developing fast solvers for linear programming relaxations of NP-hard clustering objectives. My goal is to bridge the gap between theory and practice in algorithms for graph optimization problems, in order to provide data science practitioners with methods that are fast, satisfy strong approximation guarantees, and explicitly take into account important features of the datasets that are analyzed.
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 last 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. The seminar webpage is here . You can subscribe to the Purdue Numerical Linear Algebra YouTube channel at PurdueNLA.
I frequently give local seminar talks on topics in network analysis and numerical linear algebra (often as a part of the PUNLAG seminar mentioned above). Sometimes the talks are on a specific research project I'm working on. Often though I like to take a tool or technique that has been useful in my research and present it in a way that can be more broadly applied to other projects and problems that people might be interested in. Here are some recorded talks on optimization techniques that have been useful in my work.