There are robots to sweep your floors and robots to sort packages at warehouse giants. But a Yale University professor says robots can do much more than just interact with people on a physical level — they can interact more personally, providing cues to guide social behavior.
Dr. Brian Scassellati, professor of computer science, cognitive science and mechanical engineering at Yale and direc¬tor of the National Science Foundation Expedition on Socially Assistive Robotics, will visit Missouri University of Science and Technology on Feb. 6 to deliver a lecture titled “Building Robots That Teach.”
Scassellati, who has received $10 million in funding from NSF under the program Expeditions in Computing, will speak at 10 a.m. in Room 209 in the Computer Science Building as part of the computer science department’s Distinguished Speaker Series.
“The speaker series established during our Golden Jubilee year 2015-2016 is part of our strategic vision of placing our department in top 50 in the nation,” says Dr. Sajal K. Das, the Daniel St. Clair Endowed Chair and chair of computer science. “Bringing top-notch researchers like Dr. Scassellati not only brings visibility to our institution, it also gives students and faculty a tremendous opportunity to exchange cutting-edge interdisciplinary research ideas.”
Scassellati explains some of the thinking behind his research:
“Robots have long been used to provide assistance to individual users through physical interaction, typically by supporting direct physical rehabilitation or by providing a service such as retrieving items or cleaning floors,” Scassellati says. “Socially assistive robotics (SAR) is a comparatively new field of robotics that focuses on developing robots capable of assisting users through social — rather than physical — inter¬action. Just as a good coach or teacher can provide motivation, guidance and support without mak¬ing physical contact with a student, socially assistive robots attempt to provide the appropriate emo¬tional, cognitive and social cues to encourage development, learning or therapy for an individual.”
Scassellati will discuss why physical robots are better than virtual agents for this effort. He also will highlight research in the subject and describe recent results building supportive robots that can teach social skills to children with au¬tism spectrum disorder and teach nutrition to typically developing children.
He earned a Ph.D. in computer science from the Massachusetts Institute of Technology (MIT) in 2001. He earned a bachelor of science degree in computer science, electrical engineering and brain cognitive science from MIT in 1995, and he also earned a master of science degree in computer science and electrical engineering from MIT in 1995.
Scassellati builds embodied computational models of human social behavior, especially the developmental progression of early social skills. Using computational modeling and socially interactive robots, his research evaluates models of how infants acquire social skills and assists in the diagnosis and quantification of disorders of social development, such as autism. His other interests include humanoid robots, human-robot interaction, artificial intelligence, ma¬chine perception and social learning.
He was named an Alfred P. Sloan Fellow in 2007, received an NSF CAREER award in 2003 and has earned five best-paper awards. He has been the chairman of the IEEE Autonomous Mental Development Technical Committee, the program chair of the IEEE International Conference on Development and Learning (ICDL) and the program chair for the IEEE/ACM International Conference on Human-Robot Inter¬action (HRI).
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