Maja Matarić

Maja Matarić
Matarić speaks at UCLA Library R.U.R. centennial in 2021
Born
Belgrade, Yugoslavia (now Serbia)
Alma materUniversity of Kansas (B.S.)
Massachusetts Institute of Technology (M.S., Ph.D.)
Known forSocially assistive robotics, human–robot interaction, swarm robotics
Awards
Scientific career
FieldsComputer science, Robotics, Artificial intelligence
InstitutionsUniversity of Southern California
Doctoral advisorRodney Brooks
Websitemaja-mataric.web.app

Maja Matarić is an American computer scientist. She is the Chan Soon-Shiong Endowed Chair and Distinguished Professor of Computer Science, with courtesy appointments in Neuroscience and in Pediatrics, at the University of Southern California. She is a founding pioneer of the field of socially assistive robotics,[1][2] and author of the book The Robotics Primer (MIT Press).[3]

Biography

Early Life and Education

Maja Matarić was born in Belgrade, in the former Yugoslavia, now Serbia.[4] She immigrated to the United States in her teens,[5] with her mother, Mirjana N. Matarić, who was an accomplished author and educator.[6] Her father, an electrical engineer, passed away from cancer before they immigrated.

Matarić received a Bachelor of Science degree in Computer Science from the University of Kansas in 1987, with a minor in Psychology/Cognitive Science. She received a Master of Science in Computer Science and AI in 1990 and a Doctor of Philosophy in Computer Science and AI in 1994, both from MIT. Her master's thesis was titled "A Model for Distributed Mobile Robot Environment Learning and Navigation"[7] and her doctoral dissertation was titled "Interaction and Intelligent Behavior".[8] Her master's and doctoral advisor was Prof. Rodney A. Brooks.

Career

Matarić started her academic career as an assistant professor in the Computer Science Department at Brandeis University, where she founded her Interaction Lab. She moved to the University of Southern California (USC) in 1997. At USC, she was the founding director of the USC Robotics and Autonomous Systems Center (RASC),[9] and the co-director of the USC Robotics Lab, in addition to continuing to grow her Interaction Lab.

After obtaining tenure, Matarić also became actively involved in university leadership: she served as the elected president of the faculty and the Academic Senate (2006-2007), as the Vice Dean of Research in the USC Viterbi School of Engineering (2006-2019), and then as the interim USC Vice President of Research (2019-2020). Matarić was a visiting faculty researcher at Google in 2022, and then spent her two-year sabbatical as a Principal Scientist at Google DeepMind.

Organizations

Matarić is a member of the National Academy of Engineering (NAE)[10] and the American Academy of Arts and Sciences (AMACAD).[11][12] She is a fellow of AAAS,[13] ACM,[14] AAAI,[15] and IEEE.[16] She was also the recipient of an NSF Career Award (1996) and the Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring (PAESMEM, 2011),[17] the ACM Athena Lecturer Award (2024),[18] and the ACM Eugene L. Lawler Award for Humanitarian Computing (2025),[19] among others (see Awards section below).

Research

Matarić has published extensively and is highly cited across the fields of robotics, artificial intelligence (AI), and machine learning.[20]

Behavior-Based Control and Learning

Beginning with her graduate work at MIT, Matarić made fundamental contributions to the understanding of autonomous robot cognition and interaction. For her master's degree, she was the first to demonstrate that behavior-based systems (BBS) could be endowed with representation and thus have the expressive power to plan and learn.[21][22] Her well-known robot system, Toto, was the first behavior-based system to learn maps online and optimize its behavior. It is highly cited and remains one of the milestones in BBS.[23]

Multi-Robot Coordination: Distributed Robot Teams and Swarms

In her PhD work, Matarić was one of the first to work on decentralized, distributed algorithms for robot teams and robot swarms that leveraged scalable local control. She enabled a team of 20 physical robots to interact and cooperate on tasks such as coordinated exploration, foraging, organizing in formations, and homing. Prior to her PhD work, nearly all research in robotics was restricted to single robots or pairs. She made pioneering contributions to the theory and practice of multi-robot coordination by showing that complex behaviors could be composed of basis behaviors in a principled way, bringing rigor to the then nascent discipline of distributed robotics.[8]

Matarić's next major contributions came as a faculty member, and focused on distributed robotics, also called multi-robot coordination and learning.[24] Her work provided the first formal analysis of existing multi-robot coordination approaches, elucidating formal and practical limitations, then addressed those limitations by contributing provably correct yet scalable task allocation algorithms for multi-robot control.[25] Her research group developed efficient principled market-based strategies in physical real-world validated multi-robot systems performing a variety of tasks including object transport, area cleanup, and reconnaissance.[26] Her group's work also demonstrated analytical methods for automatically generating minimalist multi-robot controllers with provable properties.[27] Finally, Matarić's research lab, the Interaction Lab, demonstrated both theoretically and experimentally the viability of online real-time learning in distributed multi-robot systems.[28] Her Interaction Lab developed algorithms for model learning within a team,[29] learning by imitation,[30] and learning through human-robot interaction.[31] She was a pioneer and an established leader in multi-robot coordination, which is now a large and thriving area of robotics.

Socially Assistive Robotics

Matarić's research since 2000 has been in the new field of socially assistive robotics (SAR), which she pioneered (with Prof. Brian Scassellati).[1][2] Socially assistive robotics aims to enable intelligent machines to help people help themselves through personalized, assistive social (rather than physical) interactions. This research both gains novel insights into human behavior through human-machine interaction and develops robotic systems that use human-robot interaction (HRI) to provide personalized assistance in convalescence, rehabilitation, training, and education.

Since 2000, Matarić's Interaction Lab has developed intelligent HRI and SAR algorithms and methods capable of real-time perception, user modeling, and learning in complex, dynamic, and uncertain human environments. Notably, Mataric's work is known for validation and evaluation with challenging beneficiary populations, including in post-stroke rehabilitation,[32][33] cognitive and social skill training for children with autism spectrum disorders,[34][35][36][37] cognitive and movement exercises for healthy elderly users[38][39] and those with Alzheimer's Disease,[40][41] attention support for studying for students with ADHD,[42] and personalized therapy for users with anxiety and/or depression.[43] This work is conducted through some of the longest studies and data collections in real-world, challenging environments such as schools, therapy centers, rehabilitation clinics, nursing homes, and private homes.

Mataric's work has the potential for major impact on the way health care is delivered to large populations, and on how affordable and accessible care, education, and training can become, through human-centered use of AI and other technologies. By focusing on human augmentation rather than automation,[44] her research has promising implications on the future of work, with broad-reaching interdisciplinary impact.

AI and Machine Learning

Mataric's entire research career has been in AI and Machine Learning (ML), from her MS thesis on learning spatial representations,[21] to her PhD work on robot teams,[8] through her lab's work on robot learning within a team,[45] learning by imitation,[46] and learning through human-robot interaction,[47] to the work on understanding human activity for human-robot interaction.[48] Her work in socially assistive systems has focused on developing personalized diagnostic and assistive and therapeutic interactions in a variety of domains (early child development,[49][50][51] autism therapy,[52] pain management,[53][54] cerebral palsy therapy,[55] ADHD and anxiety support, stroke rehabilitation, and dementia detection and support) by studying and developing models for understanding and supporting key behavioral capabilities and predictors, including personality,[56] engagement, and motivation.[57] Her work has spanned deep learning & small and large models, continuing to contribute to the rapidly evolving AI landscape.[10]

Service to the Research Community

Matarić has served the computing, AI, and robotics communities through numerous organizational committees as well as in advisory roles, including serving on the National Science Foundation CISE Advisory Committee, the Computing Community Consortium (CCC) Council,[58] the Scientific Advisory Board of the Max Planck Institute for Intelligent Systems,[59] the DARPA Information Science and Technology (ISAT) Study Group,[60] the US Scientific Advisory Council, Nature and Scientific American (Springer), and the AAAS Leshner Leadership Institute,[61] among others.

Mentoring

Matarić has had a life-long commitment to highly active mentoring and outreach. She started mentoring undergraduate students and K-12/pre-university students as an assistant professor. Throughout her career, she has mentored and placed women students and members of other underrepresented groups in graduate programs and faculty positions world-wide. She has also mentored junior women researchers via CRA programs[62] and local and national programs and panels. When serving in university leadership roles (as dean of research and then vice president of research), she established permanent university mentoring centers and programs for students and faculty.

Matarić is also an active leader in K-12 STEM outreach and innovation. For over two decades, she ran federally-funded programs that provided research experiences for both K-12 teachers and students, in order to expand their horizons about cutting edge advancements and opportunities in computing, using robotics and AI as both topics and tools for learning. She led and significantly grew the USC Viterbi School of Engineering K-12 STEM Center[63] that informed over 10,000 K-12 students and teachers per year.

In recognition of these long-standing efforts, she received the Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring from President Obama in 2011,[17] along with other mentoring awards (see Awards section).

Awards

A select list of her awards include:

Book

  • Matarić, Maja J. (2007). The Robotics Primer. MIT Press. ISBN 9780262633543.

References

  1. ^ a b Feil-Seifer, David; Matarić, Maja J. (2005). "Defining Socially Assistive Robotics". IEEE 9th International Conference on Rehabilitation Robotics: 465–468. doi:10.1109/ICORR.2005.1501143.
  2. ^ a b Matarić, Maja J.; Scassellati, Brian (2016). "Socially Assistive Robotics". Springer Handbook of Robotics.
  3. ^ Matarić, Maja J. (2007). The Robotics Primer. MIT Press. ISBN 9780262633543.
  4. ^ "ACM Bytecast Ep. 73: Maja Mataric".
  5. ^ "The Story of an Influential Advocate". Computing Research Association.
  6. ^ "Mira N. Matarić: Bio and Bibliography". 8 January 2015.
  7. ^ Matarić, Maja J. (1990). A Model for Distributed Mobile Robot Environment Learning and Navigation (M.S. thesis). MIT. hdl:1721.1/7027.
  8. ^ a b c Matarić, Maja J. (1994). Interaction and Intelligent Behavior (Ph.D. thesis). MIT. hdl:1721.1/7343.
  9. ^ "USC Robotics and Autonomous Systems Center".
  10. ^ a b "Maja Mataric Elected to the NAE". Viterbi Magazine.
  11. ^ "Maja J. Mataric". American Academy of Arts and Sciences.
  12. ^ "AMACAD Induction, Class Speaker". YouTube. 19 December 2023.
  13. ^ "AAAS Fellows Listing".
  14. ^ "Maja Mataric Named a 2020 ACM Fellow". Computing Community Consortium Blog. 15 January 2021.
  15. ^ "Elected AAAI Fellows".
  16. ^ "Engineering Our Future: Maja Mataric". IEEE.tv. 2 August 2011.
  17. ^ a b "Computer Scientist Maja Mataric Receives Presidential Mentoring Award". Computing Community Consortium Blog. 10 February 2011.
  18. ^ "ACM Athena Award: Maja Mataric".
  19. ^ "ACM Eugene Lawler Award".
  20. ^ "Maja Matarić". Google Scholar.
  21. ^ a b Matarić, Maja J. (1992). "Integration of representation into goal-driven behavior-based robots". IEEE Transactions on Robotics and Automation. 8 (3): 304–312. Bibcode:1992ITRA....8..304M. doi:10.1109/70.143349.
  22. ^ Matarić, Maja J.; Michaud, François (2008). "Behavior-Based Systems". Springer Handbook of Robotics. pp. 891–909. doi:10.1007/978-3-540-30301-5_39. ISBN 978-3-540-23957-4.
  23. ^ Matarić, Maja J. (1997). "Behaviour-based control: Examples from navigation, learning, and group behaviour". Journal of Experimental & Theoretical Artificial Intelligence. 9 (2–3): 323–336. Bibcode:1997JETAI...9..323M. doi:10.1080/095281397147149.
  24. ^ "Herd Mentality". Wired. June 1996.
  25. ^ Gerkey, Brian P.; Matarić, Maja J. (2004). "A formal analysis and taxonomy of task allocation in multi-robot systems". The International Journal of Robotics Research. 23 (9): 939–954. Bibcode:2004IJRR...23..939G. doi:10.1177/0278364904045564.
  26. ^ Gerkey, Brian P.; Mataric, Maja J. (2002). "Sold!: Auction methods for multirobot coordination". IEEE Transactions on Robotics and Automation. 18 (5): 758–768. Bibcode:2002ITRA...18..758G. doi:10.1109/TRA.2002.803462.
  27. ^ Fredslund, J.; Matarić, Maja J. (2002). "A general algorithm for robot formations using local sensing and minimal communication". IEEE Transactions on Robotics and Automation. 18 (5): 837–846. Bibcode:2002ITRA...18..837F. doi:10.1109/TRA.2002.803458.
  28. ^ Matarić, Maja J. (1997). "Reinforcement learning in the multi-robot domain". Autonomous Robots. 4 (1): 73–83. doi:10.1023/A:1008819414322.
  29. ^ Mataric, Maja J. (1994). "Reward Functions for Accelerated Learning". Machine Learning Proceedings 1994. pp. 181–189. doi:10.1016/B978-1-55860-335-6.50030-1. ISBN 978-1-55860-335-6.
  30. ^ Matarić, Maja J. (2002). "Sensory-Motor Primitives as a Basis for Imitation: Linking Perception to Action and Biology to Robotics". Imitation in Animals and Artifacts. pp. 391–422. doi:10.7551/mitpress/3676.003.0016. ISBN 978-0-262-27121-9.
  31. ^ Nicolescu, Monica N.; Mataric, Maja J. (2003). "Natural methods for robot task learning: Instructive demonstrations, generalization and practice". Proceedings of the second international joint conference on Autonomous agents and multiagent systems. pp. 241–248. doi:10.1145/860575.860614. ISBN 1-58113-683-8.
  32. ^ Tapus, Adriana (2008). "User—robot personality matching and assistive robot behavior adaptation for post-stroke rehabilitation therapy". Intelligent Service Robotics. 1 (2): 169–183. doi:10.1007/s11370-008-0017-4.
  33. ^ Matarić, Maja J. (2007). "Socially assistive robotics for post-stroke rehabilitation". Journal of Neuroengineering and Rehabilitation. 4 (1) 5. doi:10.1186/1743-0003-4-5. PMC 1821334. PMID 17309795.
  34. ^ Scassellati, Brian (2012). "Robots for use in autism research". Annual Review of Biomedical Engineering. 14 (1): 275–294. doi:10.1146/annurev-bioeng-071811-150036. PMID 22577778.
  35. ^ Feil-Seifer, David; Matarić, Maja J. (2009). "Toward Socially Assistive Robotics for Augmenting Interventions for Children with Autism Spectrum Disorders". Experimental Robotics. Springer Tracts in Advanced Robotics. Vol. 54. pp. 201–210. doi:10.1007/978-3-642-00196-3_24. ISBN 978-3-642-00195-6.
  36. ^ Jain, Shomik (2020). "Modeling engagement in long-term, in-home socially assistive robot interventions for children with autism spectrum disorders". Science Robotics. 5 (39) eaaz3791. arXiv:2002.02453. doi:10.1126/scirobotics.aaz3791. PMID 33022604.
  37. ^ Shi, Zhonghao (2022). "Toward personalized affect-aware socially assistive robot tutors for long-term interventions with children with autism". ACM Transactions on Human-Robot Interaction. 11 (4): 1–28. doi:10.1145/3526111. hdl:1721.1/146429.
  38. ^ Fasola, Juan; Matarić, Maja J. (2013). "A socially assistive robot exercise coach for the elderly". Journal of Human-Robot Interaction. 2 (2): 3–32. doi:10.5898/JHRI.2.2.Fasola.
  39. ^ Fasola, Juan; Mataric, Maja J. (2012). "Using socially assistive human–robot interaction to motivate physical exercise for older adults". Proceedings of the IEEE. 100 (8): 2512–2526. doi:10.1109/JPROC.2012.2200539.
  40. ^ Tapus, Adriana; Tapus, Cristian; Mataric, Maja J. (2009). "The use of socially assistive robots in the design of intelligent cognitive therapies for people with dementia". 2009 IEEE International Conference on Rehabilitation Robotics. pp. 924–929. doi:10.1109/ICORR.2009.5209501. ISBN 978-1-4244-3788-7.
  41. ^ Lima, M. R. (2025). "Evaluating spoken language as a biomarker for automated screening of cognitive impairment". Communications Medicine. 6 (1) 6. doi:10.1038/s43856-025-01263-1. PMC 12770543. PMID 41388139.
  42. ^ O'Connell, Amy; Banga, Ashveen; Ayissi, Jennifer; Yaminrafie, Nikki; Ko, Ellen; Le, Andrew; Cislowski, Bailey; Mataric, Maja (2024). "Design and Evaluation of a Socially Assistive Robot Schoolwork Companion for College Students with ADHD". Proceedings of the 2024 ACM/IEEE International Conference on Human-Robot Interaction. pp. 533–541. doi:10.1145/3610977.3634929. ISBN 979-8-4007-0322-5.
  43. ^ Xu, T. (2024). "Depression and anxiety detection using multimodal data". arXiv:2402.17937 [cs.RO].
  44. ^ Matarić, Maja J. (2017). "Socially assistive robotics: Human augmentation versus automation". Science Robotics. 2 (4) eaam5410. doi:10.1126/scirobotics.aam5410. PMID 33157869.
  45. ^ Mataric, Maja J. (1994). "Reward Functions for Accelerated Learning". Machine Learning Proceedings 1994. pp. 181–189. doi:10.1016/B978-1-55860-335-6.50030-1. ISBN 978-1-55860-335-6.
  46. ^ Matarić, Maja J. (2002). "Sensory-Motor Primitives as a Basis for Imitation: Linking Perception to Action and Biology to Robotics". Imitation in Animals and Artifacts. pp. 391–422. doi:10.7551/mitpress/3676.003.0016. ISBN 978-0-262-27121-9.
  47. ^ Nicolescu, Monica N.; Mataric, Maja J. (2003). "Natural methods for robot task learning: Instructive demonstrations, generalization and practice". Proceedings of the second international joint conference on Autonomous agents and multiagent systems. pp. 241–248. doi:10.1145/860575.860614. ISBN 1-58113-683-8.
  48. ^ Fod, A. (2002). "Automated derivation of primitives for movement classification". Autonomous Robots. 12 (1): 39–54. doi:10.1023/A:1013254724861.
  49. ^ Deng, Weiyang; Sargent, Barbara; Bradley, Nina S.; Klein, Lauren; Rosales, Marcelo; Pulido, Jose Carlos; Mataric, Maja J.; Smith, Beth A. (2021). "Using Socially Assistive Robot Feedback to Reinforce Infant Leg Movement Acceleration". 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN). pp. 749–756. doi:10.1109/RO-MAN50785.2021.9515537. ISBN 978-1-6654-0492-1.
  50. ^ Klein, Lauren; Itti, Laurent; Smith, Beth A.; Rosales, Marcelo; Nikolaidis, Stefanos; Matarić, Maja J. (2019). "Surprise! Predicting Infant Visual Attention in a Socially Assistive Robot Contingent Learning Paradigm". 2019 28th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN). pp. 1–7. doi:10.1109/RO-MAN46459.2019.8956385. ISBN 978-1-7281-2622-7.
  51. ^ Dust, A'di; Levitt, Pat; Matarić, Maja (2024). "Behind the Smile: Mental Health Implications of Mother-Infant Interactions Revealed Through Smile Analysis". 2024 12th International Conference on Affective Computing and Intelligent Interaction (ACII). pp. 46–54. arXiv:2408.01434. doi:10.1109/ACII63134.2024.00010. ISBN 979-8-3315-1643-7.
  52. ^ Scassellati, Brian (2012). "Robots for use in autism research". Annual Review of Biomedical Engineering. 14: 275–294. doi:10.1146/annurev-bioeng-071811-150036. PMID 22577778.
  53. ^ Trost, M. J. (2019). "Socially assistive robots for helping pediatric distress and pain: a review of current evidence". The Clinical Journal of Pain. 35 (5): 451–458. doi:10.1097/AJP.0000000000000688. PMC 6527453. PMID 30951515.
  54. ^ Trost, Margaret J.; Chrysilla, Grace; Gold, Jeffrey I.; Matarić, Maja (2020). "Socially-Assistive Robots Using Empathy to Reduce Pain and Distress during Peripheral IV Placement in Children". Pain Research and Management: 1–7. doi:10.1155/2020/7935215. PMC 7171682. PMID 32351642.
  55. ^ Dennler, Nathaniel; Yunis, Catherine; Realmuto, Jonathan; Sanger, Terence; Nikolaidis, Stefanos; Mataric, Maja (2021). "Personalizing User Engagement Dynamics in a Non-Verbal Communication Game for Cerebral Palsy". 2021 30th IEEE International Conference on Robot & Human Interactive Communication (RO-MAN). pp. 873–879. arXiv:2107.07446. doi:10.1109/RO-MAN50785.2021.9515466. ISBN 978-1-6654-0492-1.
  56. ^ Serapio-García, Gregory; Safdari, Mustafa; Crepy, Clément; Sun, Luning; Fitz, Stephen; Romero, Peter; Abdulhai, Marwa; Faust, Aleksandra; Matarić, Maja (2025). "A psychometric framework for evaluating and shaping personality traits in large language models". Nature Machine Intelligence. 7 (12): 1954–1968. doi:10.1038/s42256-025-01115-6. PMC 12719228. PMID 41438004.
  57. ^ Greczek, Jillian; Atrash, Amin; Matarić, Maja (2013). "A Computational Model of Graded Cueing: Robots Encouraging Behavior Change". HCI International 2013 - Posters' Extended Abstracts. Communications in Computer and Information Science. Vol. 374. pp. 582–586. doi:10.1007/978-3-642-39476-8_117. ISBN 978-3-642-39475-1.
  58. ^ "CCC Council Member Profile".
  59. ^ "Max Planck Scientific Advisory Board".
  60. ^ "USC Computer Science Professor Named to DARPA ISAT Study Group". Viterbi Magazine.
  61. ^ "AAAS Leshner Institute".
  62. ^ "Diversifying the Next Generation of Roboticists". CRA-WP.
  63. ^ "Viterbi K-12 STEM Center".
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