Ph.D., Applied Mathematics, UCLA, September 2010 - June 2015
B.S./M.S. (Joint Program), Applied Mathematics, UCLA,
Assistant Professor, Michigan State University August 2016 - present, Department of Mathematics and CMSE
UC President’s Postdoctoral Scholar, UCSD July 2015 - July 2016, Department of Mathematics
UC President’s Postdoctoral Fellowship (2015-2016)
Pacific Journal of Mathematics Dissertation Prize (2015)
Dissertation Year Fellowship (2014-2015)
NSF Graduate Fellowship (2011-2014)
Eugene-Cota Robles Fellowship (2010-2011)
NSF Research and Training Grant (RTG) Fellowship in Applied Mathematics (2010-2011)
Sherwood Award (for excellence in undergraduate studies) (2010)
Departmental Scholar at UCLA (2009-2010)
Basil Gordon Prize ($1000) for Putnam exam (2008)
My research consists of developing methods involving optimization for classication (clustering) using a graphical framework. The goal is to partition the data sets efficiently and accurately into a predetermined number of clusters, with or without some prior knowledge of the classication of a small percentage of the nodes. The classication problem is essential to machine learning; it occurs in numerous applications, such as medical or genomics data, spam detection, face recognition, financial predictions, and is finding growing use in text mining studies.
I have also formulated some algorithms for image processing. Processing images is also of critical importance since images and other sensing modes are crucial in procedures of a variety of fields such as medicine (i.e. MRI imaging) and engineering.