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Emanuel Todorov

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Emanuel V. Todorov
Born1971
NationalityBulgarian
Alma materWest Virginia Wesleyan College B.S. (1993)
Massachusetts Institute of Technology Ph.D. (1998)
Scientific career
FieldsNeuroscience, Artificial Intelligence,
InstitutionsUniversity of Washington
Doctoral advisorMichael I. Jordan
Whitman Richards
Websitehomes.cs.washington.edu/~todorov/

Emanuel (Emo) Vassilev Todorov (born 1971), a neuroscientist, is an associate professor and director of the Movement Control Laboratory[1] at the University of Washington. He introduced the use of optimal control as a formal explanatory framework for biological movement (see below). He is the principal developer of the MuJoCo physics engine.[2]

Todorov completed his PhD in MIT under the supervision of Michael Jordan and Whitman Richards.[3] He was a postdoctoral fellow at the Gatsby Computational Neuroscience Unit[4] at UCL under Peter Dayan and Geoffrey Hinton. He is a recipient of the 2004 Sloan Fellowship in neuroscience.[5]

In 2002 he proposed that stochastic optimal control principles are a good theoretical framework for explaining biological movement.[6] In 2011 this view was acknowledged by one of its critics, Karl Friston, to have become "the dominant paradigm for understanding motor behavior in formal or computational terms."[7] It has been described in the popular scientific press together with other connections between biology and optimisation principles.[8] An editorial comment by Kenji Doya about one of Todorov's articles in PNAS called it "a refreshingly new approach in optimal control based on a novel insight as to the duality of optimal control and statistical inference".[9]

His work on robotic hands has been featured in popular publications on robotics.[10][11][12] In January 2017 he was interviewed for the Robots Podcast.[13]

He is the recipient of 11 National Science Foundation grant awards totalling more than $7.5 million as Principal Investigator.[14]

References

  1. ^ "University of Washington faculty page". washington.edu. University of Washington. 12 June 2009. Retrieved 29 April 2017.
  2. ^ Todorov, Emanuel; Erez, Tom; Tassa, Yuval (2012). "MuJoCo: A physics engine for model-based control". 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems. International Conference on Intelligent Robots and Systems (IROS). pp. 5026–5033. doi:10.1109/IROS.2012.6386109. ISBN 978-1-4673-1736-8.
  3. ^ Studies of Goal-directed Movements (PhD). 1998. hdl:1721.1/9612.
  4. ^ "Gatsby Computational Neuroscience Unit". Gatsby.ucl.ac.uk. Retrieved 29 April 2017.
  5. ^ "List of past Sloan Fellows". sloan.org. Sloan Foundation. Retrieved 29 April 2017.
  6. ^ Todorov, Emanuel; Jordan, Michael I. (2002). "Optimal feedback control as a theory of motor coordination". Nature Neuroscience. 5 (11): 1226–1235. doi:10.1038/nn963. PMID 12404008. S2CID 205441511.
  7. ^ Friston, Karl (2011). "What Is Optimal about Motor Control?". Neuron. 72 (3): 488–498. doi:10.1016/j.neuron.2011.10.018. PMID 22078508.
  8. ^ Angier, Natalie (1 November 2010). "Optimization at the Intersection of Biology and Physics". The New York Times. Retrieved 6 May 2017.
  9. ^ Doya, Kenji (2009). "How can we learn efficiently to act optimally and flexibly?". PNAS. 106 (28): 11429–11430. Bibcode:2009PNAS..10611429D. doi:10.1073/pnas.0905423106. PMC 2710651. PMID 19584249.
  10. ^ Schmerler, Jessica; Chant, Ian (1 July 2016). "Tomorrow's Prosthetic Hand". Scientific American Mind. Retrieved 6 May 2017.
  11. ^ "This Is the Most Amazing Biomimetic Anthropomorphic Robot Hand We've Ever Seen". IEEE Spectrum, Evan Ackerman, 18 Feb 2016
  12. ^ "UW team creates robotic hand that learns to become more dexterous than yours". GeekWire, Alan Boyle, May 9, 2016
  13. ^ "Robots Podcast : Physics-based Optimization for Robot Control, with Emo Todorov". Irish Tech News, Simon Cocking January 20, 2017.
  14. ^ "National Science Foundation grants awarded to Emanuel Todorov". nsf.gov. NSF. Retrieved 29 April 2017.
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