Heather Pon-Barry

  • Associate Professor of Computer Science
  • on leave fall 2022
Heather Pon-Barry

Heather Pon-Barry’s research focuses on human-robot interaction and spoken dialogue. It combines elements of artificial intelligence, computational linguistics, signal processing and cognitive science. Pon-Barry develops technologies that augment traditional speech and vision perception—analyzing the intonation patterns of speech and visual information to allow social robots to better converse with humans. Much of her work focuses on educational applications of robots and dialogue systems.

Pon-Barry also works on activities to broaden participation in computer science, including the development of MaGE (Megas and Gigas Educate). The MaGE curriculum and peer mentorship program focuses on inclusion as a key tool for creating a welcoming environment that fosters a community of learning, especially for students who may not see themselves reflected in the existing computer science community.

Her work has been supported by a National Science Foundation CAREER award, a NSF National Robotics Initiative award, and a Google CS Capacity Award. Pon-Barry earned a doctorate in computer science from Harvard University. She first began studying spoken dialogue as an undergraduate and master’s student in Symbolic Systems (cognitive science) at Stanford University. At Mount Holyoke, she teaches courses in natural language processing, introductory computer science, data structures, and a seminar on talking robots.

Areas of Expertise

Spoken language processing, emotion recognition, human-robot interaction, artificial intelligence, computational linguistics, cognitive science

Education

  • Ph.D., Harvard University
  • M.S., B.S., Stanford University

HAPPENING AT MOUNT HOLYOKE

Recent Campus News

Spurred by the mentoring of Mount Holyoke professors, Lydia Cheah ’20 has found herself leading the way to reshape the computer science career track.

Mount Holyoke professor Valerie Barr ’77 is a recipient of an NSF grant that funds a multi-institution collaboration toward diversity in computer science.

The Mount Holyoke College Board of Trustees has voted to grant tenure to nine faculty members spanning disciplines from gender studies to physics.

Recent Grants

Heather Pon-Barry (Computer Science) received a National Science Foundation grant for her project 'CAREER: Dialogue Engagement for Educational Robots.' The project is for five years. (2020)

Audrey St. John, Heather Pon-Barry and Becky Wai-Ling Packard received a Microsoft Corporation grant for the project "Development of Core Modules as Curricular Assets for Tech Mentorship Initiative." The project is for 2.5 months. Combined award to Audrey St. John (Computer Science), Heather Pon-Barry (Computer Science) and Becky Packard (Psychology and Education).

Recent Publications

Lubold, N., Walker, E., & Pon-Barry, H. (2021). Effects of Adapting to User Pitch on Rapport Perception, Behavior, and State with a Social Robotic Learning Companion. User Modeling and User-Adapted Interaction, 31: 35-73.

Lubold, N., Walker, E., Pon-Barry, H., & Ogan, A. (2019). Comfort with Robots Influences Rapport with a Social, Entraining Teachable Robot. In Proceedings of the International Conference on Artificial Intelligence in Education.

Chaffey, T., Kim, H., Nobrega, E., Lubold, N., & Pon-Barry, H. (2018). Dyadic Stance in Natural Language Communication with a Teachable Robot. In HRI '18 Companion: 2018 ACM/IEEE International Conference on Human-Robot Interaction, pp. 85–86.

Das, R. & Pon-Barry, H. (2018). Turn-taking strategies for human-robot peer-learning dialogue. In Proceedings of the 19th Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL), pp. 119-129, Melbourne, Australia, July 2018.

Lubold, N., Walker, E., Pon-Barry, H., & Ogan, A. (2018). Automated Pitch Convergence Improves Learning in a Social, Teachable Robot for Middle School Mathematics. In Proceedings of Artificial Intelligence in Education (AIED).

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