Radford M. Neal (born September 12, 1956) is a professor emeritus at the Department of Statistics and Department of Computer Science at the University of Toronto, where he holds a research chair in statistics and machine learning.

Radford M. Neal
Born (1956-09-12) September 12, 1956 (age 68)[1]
CitizenshipCanadian
EducationUniversity of Calgary
University of Toronto
Scientific career
FieldsStatistics, Machine Learning, Artificial Intelligence
InstitutionsUniversity of Toronto
ThesisBayesian Learning for Neural Networks (1995)
Doctoral advisorGeoffrey Hinton
Other academic advisorsDavid Hill
Websitewww.cs.utoronto.ca/~radford/

Education and career

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Neal studied computer science at the University of Calgary, where he received his B.Sc. in 1977 and M.Sc. in 1980, with thesis work supervised by David Hill. He worked for several years as a sessional instructor at the University of Calgary and as a statistical consultant in the industry before coming back to the academia. Neal continued his study at the University of Toronto, where he received his Ph.D. in 1995 under the supervision of Geoffrey Hinton.[2] Neal became an assistant professor at the University of Toronto in 1995, an associated professor in 1999 and a full professor since 2001. He was the Canada Research Chair in Statistics and Machine Learning from 2003 to 2016 and retired in 2017.

Neal has made great contributions in the area of machine learning and statistics, where he is particularly well known for his work on Markov chain Monte Carlo,[3][4] error correcting codes[5] and Bayesian learning for neural networks.[6] He is also known for his blog[7] and as the developer of pqR: a new version of the R interpreter.[8]

Bibliography

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Books and chapters

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  • Neal, Radford M. (1996). Bayesian learning for neural networks. New York: Springer. ISBN 0-387-94724-8. OCLC 34894370.
  • Neal, Radford M. (2011-05-10). Brooks, Steve; Gelman, Andrew; Jones, Galin; Meng, Xiao-Li (eds.). MCMC using Hamiltonian dynamics. arXiv:1206.1901. Bibcode:2011hmcm.book..113N. doi:10.1201/b10905. ISBN 9780429138508. S2CID 1048042.

Selected papers

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References

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  1. ^ "Radford M. Neal Curriculum Vitae" (PDF). User radford at cs.utoronto.ca. Retrieved 4 May 2015.
  2. ^ Neal, Radford M. (2022-05-31). "Curriculum Vitae" (PDF).
  3. ^ Neal, Radford (1993). Probabilistic Inference Using Markov Chain Monte Carlo Methods (PDF) (Report). Technical Report CRG-TR-93-1, Department of Computer Science, University of Toronto. p. 144. Retrieved 9 May 2015.
  4. ^ Neal, Radford M (2011). "MCMC Using Hamiltonian Dynamics" (PDF). In Steve Brooks; Andrew Gelman; Galin L. Jones; Xiao-Li Meng (eds.). Handbook of Markov Chain Monte Carlo. Chapman and Hall/CRC. ISBN 978-0470177938.
  5. ^ MacKay, D. J. C.; Neal, R. M. (1996). "Near Shannon limit performance of low density parity check codes". Electronics Letters. 32 (18): 1645. Bibcode:1996ElL....32.1645M. doi:10.1049/el:19961141.
  6. ^ Neal, R. M. (1996). Bayesian Learning for Neural Networks. Lecture Notes in Statistics. Vol. 118. doi:10.1007/978-1-4612-0745-0. ISBN 978-0-387-94724-2.
  7. ^ "Radford Neal's blog". Retrieved 9 May 2015.
  8. ^ "pqR - a pretty quick version of R". Retrieved 9 May 2015.