My discipline is computer science. This field is large and relatively new amongst the sciences. Within this field, the subfield that interests me most is Artificial Intelligence (AI). This area has suggested having strong promises since its infancy in the 1950s. However, in present day we are finally able to its usefulness actualize: from autonomous vehicle navigation, a myriad of recognition systems (such as speech, face, hand-writing, eye, etc), anomaly detection, game playing (such as chess system Deep Blue), classification schemes, and even prediction systems related to stock markets or which music CD we will likely be interested in buying.

Artificial Intelligence is primarily concerned with the ability and task to make computers think abstractly--to have intelligence. For example, can we develop a system that never loses against a human player in a game of tic-tac-toe? Sure, AI could be used; we could program a computer to KNOW all the rules of tic-tac-toe ahead of time and to appropriately move such that it will never lose. However, a system that has the ability to learn from its past behavior possesses a higher level of abstraction. This sub/related field of AI is called machine learning and interests me most.

Within machine learning, the areas and problems about which I am most curious are planning, decision-making within uncertain environments, reinforcement learning, and information retrieval.

Dr. Philip Chan was my first research advisor, and throughout my three years of undergraduate research he served as a good mentor who demonstrated to me the nature and way to conduct sound research. My past projects are outlined below:


Adaptive Web Personalization:

For sixteen months I have researched adaptive web personalization. Specifically, my research advisor and I have been interested in finding intrinsic, non-invasive ways to model a web user's behavior so as to accurately predict what she is interested in. Using only a web user's bookmarked web pages, I developed a system that evaluates and ranks web pages comparably well to that of Google's ranking. Moreover, with the useful information of a given Google ranking, and appropriately combining it with our respective ranking, our system outperforms that of Google's ranking alone.

Speech Recognition:

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NASA Anomaly Detection:

During the summer after my sophomore year, I was introduced to artificial intelligence while serving as a researcher on a  NASA-funded anomaly detection project. As the only undergraduate on the four-person team, I was responsible for exploring ways to dynamically model data that are to be considered "normal" This sixteen-month-long project provided me with both an understanding of how research is conducted and with the technical knowledge that included clustering, statistics, distance measurements, and ROC curves. Ultimately, I contributed toward providing NASA with my team's patent-pending product.