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Branimir Boguraev

Branimir Boguraev works in the area of question analysis – identifying prominent content from questions and available sources to decipher the quality of possible answers.

Eric Brown

Eric Brown works on the design and implementation of DeepQA architecture, as well as algorithms for special question processing.

Jennifer Chu-Carroll

Jennifer Chu-Carroll works on algorithms for identifying relevant question content in order to generate possible answers, as well as on special question processing.

Bonaventura Coppola

Bonaventura Coppola focuses on development and optimization of semantic analysis algorithms to improve DeepQA performance.

James Fan

James Fan focuses on natural language processing algorithms that help Watson find and evaluate possible answers.

David Gondek

David Gondek’s primary role is developing machine learning algorithms and infrastructure, which are used for ranking and estimating confidence in possible answers.

Aditya Kalyanpur

Aditya Kalyanpur develops a variety of algorithms for DeepQA components including answer type recognition, relation detection, spatial-temporal reasoning and learning from revealed answers.

Adam Lally

Adam Lally is responsible for the high-speed implementation of DeepQA architecture, as well as developing algorithms for understanding questions and categories.

Anthony Levas

Anthony Levas develops components that allow Watson to make sense of the context of question terms and phrases. He also works to apply DeepQA architecture to new applications.

Michael McCord

Michael McCord works on algorithms that parse the texts of both questions and answer source texts to help Watson process natural language and form its answers.

Bill Murdock

Bill Murdock helps Watson distinguish correct answers from wrong answers by building components that apply logic, learning, and analogy to the results of natural language processing.

Siddharth Patwardhan

Siddharth develops algorithms for various components within the DeepQA system, including temporal reasoning, question decomposition, lexical constraint recognition and answer type recognition.

John Prager

John Prager works in question analysis and categorization, developing algorithms for special question processing that handle such things as wordplay.

Chang Wang

Chang Wang develops relation detection algorithms for DeepQA. Chang has a background in Representation Learning, Transfer Learning and Manifold Learning.

Chris Welty

Chris Welty works on integrating semantic web applications with machine learning and natural language processing to generate and classify possible answers.

Wlodek Zadrozny

Wlodek Zadrozny works on preparing natural language sources for Watson’s database. He is also involved in adapting DeepQA technology to address business problems in different industries.