I am currently a postdoctoral research associate at the University of Illinois at Chicago studying the behavior of an incredibly hot and dense state of matter known as the Quark-Gluon Plasma (QGP). We have observed evidence of QGP production at both the Relativistic Heavy Ion Collider at Brookhaven National Lab, as well as at the CERN Large Hadron Collider. I am currently a member of the CMS Collaboration at the CERN LHC.
As part of my research (and outside of it) I'm very interested in computational methodologies, particularly applications of machine learning and "big data" analytics. I've been using some simple machine learning techniques including Boosted Decision Trees and Neural Networks in order to optimize some of the criteria used to identify certain subprocesses in our collision data from the LHC. Outside of physics, I'm working on some demo projects involving maximizing efficiency of a 3x3 road grid, where each intersection has a stoplight. Though stoplights are not the best solution to a densely populated grid, maximization of such structures can dramatically increase vehicle throughput with almost no cost and no construction.
Feel free to checkout my github repository for the raw code to some of my projects, or have a look at some of the demos on the Projects page.