
Abstract: Graduate students tend to generate a lot of data, both to understand their new ideas and to demonstrate to others which of their ideas work well. It is often tempting to display this data in an easy-to-create raw format such as a table filled with numbers. Unfortunately, such formats fail to truly show the information that the data provides, because it is difficult to see trends in a mess of raw numbers. Luckily, there are many effective techniques for displaying data graphically that allow us to quickly and clearly see what is really going on. I will present a set of useful methods for plotting data along with a brief introduction to the tools that I have used in my own research to help me see the results of the many, many experiments that I have run over my career as a graduate student.
From the fall of 2008 to the fall of 2012, I was a research assistant for Professor Wheeler Ruml. During this time, I did research on parallel heuristic search, disk-based heuristic search, hierarchical search, state space size estimation, continual planning with goal arrivals, and robot motion planning.
During the summer of 2011 I worked as an intern at the Palo Alto Research Center (PARC). While there, I did research with Dr. Rong Zhou on parallel search for model checking with the Spin model checker.
I have been a teaching assistant at the University of New Hampshire for a variety of courses including: Algorithms (2010), Introduction to Artificial Intelligence (2009), and Object-oriented Methodology (2006-2008).
I worked for the UNH-IOL for most of my undergraduate and master's degrees. While I was at the IOL I worked in the following consortia:
Some useful configuration files: