I've been involved in the creation of software for most of my life, and I still build and manage my own computers and network equipment. Google Patents has a nice listing of the patents issued to me for Internet browser technology and computer operating system security advancements.

But my tenure in the corporate world encouraged me to spend more of my time working on public interest causes. I studied at Harvard and was a fellow with the Program for Networked Governmence -- a Harvard social networking research group.

While working towards my Masters degree at the John F. Kennedy School of Government, I began to develop an interest in advancing productivity in education and academic research. One way this manifests itself in my work is through the development of new methods for use by social scientists. Despite the rapidly increasing amount of text for people to read (especially around elections and policy), we still teach undergrads to read it line by line instead of using more sophisticated methods of filtering and searching it.

I frame this effort as a bridge between qualitative context analysis and empirical analysis methods. In the past, people that crunch numbers haven't worked on content analysis of (political) communication because it is viewed as hard work with minimal payoff. I’ve found that using machine learning and natural language processing methods can resolve these workload problems.

My shift to Information Science (with a Computer Science Minor specialization in Machine Learning/Natural Language Processing) at Cornell,was a part of my realization that my work is applicable across a range of social science research projects in several disciplines.I've found that Cornell fosters unsurpassed relationships between social science researchers and engineers. In addition, the school has a unique and long history of outstanding research scientists in machine learning, information retrieval, and natural language processing. This new environment productively fosters my unique interests inline with the school's motto: "any person can find instruction in any study".

In my first year at Cornell, I worked on e-government research with NLP as a part of Claire Cardie's research group. Thorsten Joachims functioned as my advisor, although he will transition to my minor committee member in Computer Science. My Computer Science minor specialized in machine learning/data mining/applications in NLP. Claire will take over as my advisor as my education shifts from methods to applications.

As I mentioned, prior to my return to academia, I worked on software development projects in a range of software engineering and product management positions. I still work as a software development consultant for a few technology startups in Seattle and Boston. This experience lends a practical side to my academic research. I still highly value producing tools which people benefit from each day.

Academic Degrees:

• Harvard University, Master of Public Policy.
• University of Washington, Bachelor of Arts, Political Science