University of Minnesota
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Rachel Bellamy, Ph.D.

Photo of Rachel Bellamy, Ph.D.
Biography: 
Rachel is a Principle Research Scientist and manages the Human-AI Collaboration group at IBM T J Watson Research Center, Yorktown Heights, New York. In these roles, she leads an interdisciplinary team of human-computer interaction experts, user experience designers and user experience engineers. Her team is currently working on the user experience for several of IBM Research’s AI projects, including the AI Fairness 360 toolkit and rule-based machine-teaching for Watson Assistant. Rachel received her doctorate in cognitive psychology from University of Cambridge, UK in 1991. She received a Bachelor of Science in psychology with mathematics and computer science from University of London in 1986. Before coming to IBM Research, she worked in Apple Computer's Advanced Technology Group, where she conducted research on collaborative learning and led an inter-disciplinary team that worked with the San Francisco Exploratorium and schools to pioneer the design, implementation and use of media-rich collaborative learning experiences for K-12 students. She holds many patents and has published more than 70 research papers.

Recent Presentations

Fair AI in Practice

Fairness is an increasingly important concern as machine learning models are used to support decision making in high-stakes applications such as mortgage lending, hiring, and prison sentencing. This talk will introduce an open source Python toolkit for algorithmic fairness, AI Fairness 360 (AIF360). The main objectives of this toolkit are to help facilitate the transition of fairness research algorithms to use in an industrial setting and to provide a common framework for fairness researchers to share and evaluate algorithms.