I'm an Information Science Ph.D. student at Cornell University where I perform analyses on terabyte scale data sets and conduct crowdsourced experiments to enhance web search systems. My training is in machine learning, natural language processing, statistics, human computer interaction, economics, public policy, and political science.

In addition to work on web search, I use the methods developed in my dissertation for investment analysis, arbitrage opportunity discovery, and statistical arbitrage. I also have an avocation for cooking with data.

Finally, my research and teaching are motivated by my work history with information technology. Since 1990, I’ve worked in a variety of positions, including both software engineering and product management. I enjoy working with students with the drive to imagine and deliver innovative systems. This focus draws students enrolled in MBA, Information Science, and Computer Science programs to work with me on diverse projects with an underlying component that requires machine learning for a subjective or fuzzy problem. Fun student experiments include Seamless Receipts, Twitter Search for Emotional Content and augmented reality on mobile devices.

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