Rosalind Wright Picard (born 1962) is an American electrical engineer and computer scientist who is the Grover M. Hermann Professor of Health Sciences and Technology at the Massachusetts Institute of Technology (MIT). She is the founder and director of the Affective Computing Research Group at the MIT Media Lab, and co-founder of the startups Affectiva and Empatica. Prior to joining the MIT faculty, Picard worked from 1984-1987 as a Member of the Technical Staff at AT&T Bell Labs in Holmdel Township, New Jersey, first developing new VLSI-scale computer architectures for future high-speed signal processing chips and later researching new kinds of algorithms for image compression. She has received many recognitions for her research and inventions in wearable and affective computing. In 2005, she was named a Fellow of the Institute of Electrical and Electronics Engineers for contributions to image and video analysis and affective computing. In 2019 she received one of the highest professional honors accorded an engineer, election to the National Academy of Engineering for her contributions on affective computing and wearable computing. In 2021 she was recognized as a Fellow of the ACM for contributions to physiological signal sensing for individual health and wellbeing. In 2021 she was elected to the National Academy of Inventors, which recognizes outstanding inventions that have made a tangible impact on quality of life, economic development and the welfare of society. In 2022 she was awarded the International Lombardy Prize for Computer Science Research, which carries a €1 million award, which she donated to support digital health and neurology research to help save the lives of people with epilepsy and children susceptible to sudden infant death syndrome. In 2026, she received one of the Institute of Electrical and Electronics Engineers's highest honors, the IEEE Medal for Innovations in Healthcare Technology for pioneering wearable affective computing. Picard is credited with starting the branch of computer science known as affective computing with her 1997 book of the same name. This book described the importance of emotion in intelligence, the vital role human emotion communication has to relationships between people, how robots and wearable computers might perform emotion recognition and other skills of emotional intelligence, and concerns raised by this new technology. Her work in this field has led to an expansion into autism research and developing devices that could help humans recognize nuances in human emotions and provide objective data for improving healthcare.
With Jonathan Klein, she also published a presentation and discussion of many potential uses, together with concerns and objections, regarding the deployment of affective technology to address emotional needs; in particular, they called out concerns about the potential misuse of technology to manipulate people.
Academics Picard received a bachelor's degree in electrical engineering from the Georgia Institute of Technology in 1984. She received a Master of Science in 1986 and a Doctor of Science in 1991, both in electrical engineering and computer science from the Massachusetts Institute of Technology. Her doctoral dissertation was titled Texture modeling: Temperature effects on Markov/Gibbs random fields. Picard has been a member of the faculty at the MIT Media Laboratory since 1991, with tenure since 1998 and a full professorship since 2005. Picard is a researcher in the field of affective computing and the founder and director of the Affective Computing Research Group at the MIT Media Lab. The Affective Computing Research Group develops tools, techniques, and devices for sensing, interpreting, and processing signals related to emotion that drive state-of-the-art systems that respond intelligently to human emotional states. Applications of their research include physiological sensors used in medical studies and treatments and assistive technology for use in addressing the verbal communications difficulties experienced by individuals with autism. She also works with Sherry Turkle and Cynthia Breazeal in the field of social robots, and has published significant work in the areas of digital image processing, pattern recognition, and wearable computers. Picard's former students include Steve Mann, professor and researcher in wearable computers. Picard was the founding Faculty Chair of the MIT MindHandHeart Initiative, a "coalition of students, faculty, and staff [...] working collaboratively and strategically to strengthen the fabric of [the] MIT community".
Affective computing As she began building systems to objectively measure emotion in people, including wearable and computer vision and audition technologies, she described a need for more research on an area of computing inspired by the rational roles emotion plays in the human brain. She wrote a book envisioning and describing this research, including laying out how to give skills of emotional intelligence to machines, titling the book "Affective Computing". MIT's press release for Picard's book states, "According to Rosalind Picard, if we want computers to be genuinely intelligent and to interact naturally with us, we must give computers the ability to recognize, understand, even to have and express emotions". Picard explains the need to monitor emotional cues and how this is present with humans when she states:
"Whatever his strategy, the good teacher detects important affective cues from the student and responds differently because of them. For example, the teacher might leave subtle hints or clues for the student to discover, thereby preserving the learner's sense of self-propelled discovery. Whether the subject matter involves deliberate emotional expression as is the case with music, or is a "non-emotional" topic such as science, the teacher that attends to a student's interest, pleasure, and distress is perceived as more effective than the teacher that proceeds callously. The best teachers know that frustration usually precedes quitting, and know how to redirect or motivate the pupil at such times. They get to know their student, including how much distress that student can withstand before learning breaks down." But such emotional cues are not part of robotic intelligence. In order to portray how such a recognition would alter interactions with robots, Picard gave an example situation:
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