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Rosalind Picard

M.I.T. Media Laboratory, U.S.A.


Rosalind W. Picard is founder and director of the Affective Computing Research Group at the Massachusetts Institute of Technology (MIT) Media Laboratory and is co-director of the Things That Think Consortium, the largest industrial sponsorship organization at the lab. She holds a Bachelors in Electrical Engineering with highest honors from the Georgia Institute of Technology, and Masters and Doctorate degrees, both in Electrical Engineering and Computer Science, from the Massachusetts Institute of Technology (MIT). She has been a member of the faculty at the MIT Media Laboratory since 1991, with tenure since 1998. Prior to completing her doctorate at MIT, she was a Member of the Technical Staff at AT&T Bell Laboratories where she designed VLSI chips for digital signal processing and developed new methods of image compression and analysis.

The author of over a hundred peer-reviewed scientific articles in multidimensional signal modeling, computer vision, pattern recognition, machine learning, and human-computer interaction, Picard is known internationally for pioneering research in affective computing and, prior to that, for pioneering research in content-based image and video retrieval. She is recipient (with Tom Minka) of a best paper prize for work on machine learning with multiple models (1998) and is recipient (with Barry Kort and Rob Reilly) of a "best theory paper" prize for their work on affect in human learning (2001). Her award-winning book, Affective Computing, (MIT Press, 1997) lays the groundwork for giving machines the skills of emotional intelligence. She and her students have designed and developed a variety of new sensors, algorithms, and systems for sensing, recognizing, and responding respectfully to human affective information, with applications in human and machine learning, health, and human-computer interaction. She was named a Fellow of the IEEE in November 2004.

Picard has served on many science and engineering program committees, editorial boards, and review panels, and is presently serving on the Editorial Board of User Modeling and User-Adapted Interaction: The Journal of Personalization Research, as well as on the advisory boards for the National Science Foundation's division of Computers in Science and Engineering (CISE) and for the Georgia Tech College of Computing.

Picard works closely with industry, and has consulted with companies such as Apple, AT&T, BT, HP, i.Robot, and Motorola. She has delivered keynote presentations or invited plenary talks at over fifty science or technology events, and distinguished lectures and colloquia at dozens of universities and research labs internationally. Her group's work has been featured in national and international forums for the general public, such as The New York Times, The London Independent, Scientific American Frontiers, NPR's Tech Nation and The Connection, ABC's Nightline and World News Tonight with Peter Jennings, Time, Vogue, Voice of America Radio, New Scientist, and BBC's "The Works" and "The Big Byte." Picard lives in Newton, Massachusetts with her husband and three energetic sons.

Abstract

Building an Affective Learning Companion

Rosalind W. Picard
MIT Media Laboratory 20 Ames St.; Cambridge, MA 02139
[email protected] http://affect.media.mit.edu

About a half century ago, the computer became a model, metaphor and modelling tool privileging the cognitive over the affective, and engendering theories in which thinking and learning are viewed as information processing and affect is ignored or marginalised. In the last decade there has been an acceleration in efforts to redress this imbal­ance, developing technologies that can begin to measure and manage the role of affect, enabling new theories and interventions in which af­fect and cognition are appropriately integrated with one another. This invited keynote presents a vision for developing an automated learning companion that jointly supports a learner’s affective and cognitive needs. In particular, I will describe our efforts at MIT to invent several of the affective technologies to enable such a learning companion. The talk will show examples of the state of the art with respect to affect sensing and recognition and with respect to developing strategies for responding in­telligently to learner affect.

Key words: Affect recognition, affective tutor, empathetic agents, frus­tration, learner emotion

Acknowledgments. I would like to thank past and present members of the MIT Affective Computing group for their many contributions designing and de­veloping new kinds of technologies. Examples in this presentation result from collaborations with Ashish Kapoor, Win Burleson, Rana el Kaliouby, Carson Reynolds, Marc Strauss, Selene Mota, Hyungil Ahn, Shaundra Daily, Yuan Qi, John Rebula, Barry Kort, and Rob Reilly. We are indebted to Ken Perlin and John Lippincott for their development of the agent character shown in this talk. I would also like to gratefully acknowledge collaboration with Art Graesser’s group at Memphis. This work has been supported in part by the National Science Foun­dation under ITR 0325428, by the Media Lab Things That Think consortium, and by funds from NASA provided through Ahmed Noor. Any opinions, find­ings, conclusions, or recommendations expressed in this presentation are those of the presenter and do not necessarily reflect the views of the National Science Foundation or the offcial policies, either expressed or implied, of the sponsors or of the United States Government. 

 
 

Research Center for Science and Technology for Learning
National Central University