A while back, I used to be a graduate student in the Department
of Computer Sciences at the University
of Texas at Austin. I was a key member of the Knowledge Systems Research
Group headed by Bruce Porter.
Education: Ph.D., Computer Sciences, The University of Texas at Austin (2009)
Advisor: Bruce Porter
Dissertation title: Addressing the Brittleness of Knowledge-Based Question-Answering
Dr. Chaw received his Ph.D. in Computer Science from the University of Texas at Austin. He has a background in knowledge representation and reasoning(KR&R), natural language processing(NLP), and applied machine learning. Over the years, he has developed a successful track record in building transformative prototypes.
His dissertation studied methods at addressing the problem faced by users in using unfamiliar knowledge bases to answer questions. During this time, he built the ASKME research prototype, which is an integral component to support question-answering in Project Halo. External evaluations have shown the work to make significant progress towards helping users use unfamiliar knowledge bases to answer questions.
While at UT-Austin, Dr. Chaw also investigated the feasibility of using off-the-shelf KR&R and NLP technologies to automatically enrich existing knowledge bases from text. As part of this work, he helped design and build a simple learning by reading system, which was able to develop conceptual models by extracting important knowledge from texts.
After finishing his PhD, Dr. Chaw joined IBM Research to work on extending the capabilities of the Watson DeepQA system. He continued to investigate methods that learn to extract knowledge from text, a key requirement for the Watson system. During this time, he has also worked on question analysis, problem-solving methods, and contributed to a computational resource of common sense knowledge. A while back, Watson was showcased on national television by competing as a contestant on the Jeopardy! game-show.
Along with three other systems, Project Halo and Watson were both selected by AI Magazine as representing the state of the art for automatic question-answering systems.
Dr. Chaw is currently a member of the Core Relevance and Ranking team at Microsoft Bing. He has significant practical experience with web search relevance and have contributed to systems that use machine learning and online metrics to improve customer experience and the bottom line.
Department of Computer Science
The University of Texas at Austin
Email: jchaw (at) cs.utexas.edu