Stephen Muggleton

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Stephen Muggleton
NewFellowPhoto.jpg
Stephen Muggleton 2010
Born (1959-12-06) 6 December 1959 (age 55)
Fields
Institutions
Alma mater University of Edinburgh
Thesis Inductive acquisition of expert knowledge (1987)
Doctoral advisor Donald Michie[2]
Doctoral students
Known for
Notable awards
Website
www.doc.ic.ac.uk/~shm

Stephen H. Muggleton FBCS, FIET, FAAAI,[6] FREng[7] (born 6 December 1959) is Head of the Computational Bioinformatics Laboratory at Imperial College London.[1][8][9][10][11][12][13]

Education[edit]

Muggleton received his Bachelor of Science degree in Computer Science (1982) and Doctor of Philosophy in Artificial Intelligence (1986) supervised by Donald Michie at the University of Edinburgh.[14]

Career[edit]

Following his PhD, Muggleton went on to work as a postdoctoral research associate at the Turing Institute in Glasgow (1987–1991) and later an EPSRC Advanced Research Fellow at Oxford University Computing Laboratory (OUCL) (1992–1997).[15] In 1997 he took a post at the University of York and in 2001, he moved from there to Imperial College London.

Research[edit]

Muggleton's research interests[16][9] are primarily in Artificial intelligence. From 1997–2001 he held the Chair of Machine Learning at the University of York[17] and from 2001–2006 the EPSRC Chair of Computational Bioinformatics at Imperial College in London. Since 2007 he holds the Royal Academy of Engineering Research Chair[18] as well as the post of Director of Modelling for the Imperial College Centre for Integrated Systems Biology.[18] He is known for founding the field of Inductive logic programming.[19][20][21][22] In this field he has made contributions to theory introducing predicate invention, inverse entailment and stochastic logic programs. He has also played a role in systems development where he was instrumental in the systems Duce, Golem and Progol[23][24] and applications — especially biological prediction tasks.

He worked on a Robot Scientist together with Stephen Emmott[25] that would be capable of combining inductive logic with probabilistic reasoning.[26]

References[edit]

  1. ^ a b List of publications from Google Scholar
  2. ^ a b Stephen Muggleton at the Mathematics Genealogy Project
  3. ^ Moyle, Stephen Anthony (2003). An investigation into theory completion techniques in inductive logic programming (PhD thesis). University of Oxford. 
  4. ^ Santos, Jose Carlos Almeida (2010). Efficient learning and evaluation of complex concepts in inductive logic programming (PhD thesis). Imperial College London. 
  5. ^ http://www.raeng.org.uk/about/fellowship/fellowslist.htm List of Fellows of the Royal Academy of Engineering
  6. ^ http://www.aaai.org/Awards/fellows-list.php
  7. ^ http://www.raeng.org.uk/research/researcher/chairs/currentapp.htm Research Chairs: Current and Recently Completed at the Royal Academy of Engineering
  8. ^ "Professor Stephen H. Muggleton". Academic staff list. Imperial College. Retrieved 8 August 2010. 
  9. ^ a b List of publications from the DBLP Bibliography Server
  10. ^ Grants awarded to Stephen Muggleton by the Engineering and Physical Sciences Research Council
  11. ^ Stephen Muggleton from the Scopus bibliographic database.
  12. ^ Srinivasan, A.; Muggleton, S.H.; Sternberg, M.J.E.; King, R.D. (1996). "Theories for mutagenicity: A study in first-order and feature-based induction". Artificial Intelligence 85: 277. doi:10.1016/0004-3702(95)00122-0. 
  13. ^ Stephen Muggleton from the ACM Portal
  14. ^ Muggleton, Stephen (1987). Inductive acquisition of expert knowledge (PhD thesis). University of Edinburgh. 
  15. ^ Muggleton, S. (1997). "Learning from positive data" 1314. pp. 358–376. doi:10.1007/3-540-63494-0_65. 
  16. ^ List of publications from Microsoft Academic Search
  17. ^ Muggleton, S. (1999). "Scientific knowledge discovery using inductive logic programming". Communications of the ACM 42 (11): 42. doi:10.1145/319382.319390. 
  18. ^ a b "Prof Stephen Muggleton". The Royal Institution of Great Britain. Retrieved 8 August 2010. 
  19. ^ Muggleton, S.; De Raedt, L. (1994). "Inductive Logic Programming: Theory and methods". The Journal of Logic Programming. 19-20: 629–679. doi:10.1016/0743-1066(94)90035-3. 
  20. ^ Muggleton, S. (1991). "Inductive logic programming". New Generation Computing 8 (4): 295–318. doi:10.1007/BF03037089. 
  21. ^ Muggleton, S. (1995). "Inverse entailment and progol". New Generation Computing 13 (3–4): 245–286. doi:10.1007/BF03037227. 
  22. ^ Muggleton, S.; Page, D.; Srinivasan, A. (1997). "An initial experiment into stereochemistry-based drug design using inductive logic programming". Inductive Logic Programming. Lecture Notes in Computer Science 1314. p. 23. doi:10.1007/3-540-63494-0_46. ISBN 978-3-540-63494-2. 
  23. ^ "Golem". AI Japanese Institute for Science. Retrieved 8 August 2010. 
  24. ^ Michalski, R.; Tecuci, G. (1994). Machine learning: a multistrategy approach (Book). Morgan Kaufmann. p. 780. ISBN 0-934613-09-5. Retrieved 8 August 2010. 
  25. ^ King, R. D.; Whelan, K. E.; Jones, F. M.; Reiser, P. G. K.; Bryant, C. H.; Muggleton, S. H.; Kell, D. B.; Oliver, S. G. (2004). "Functional genomic hypothesis generation and experimentation by a robot scientist". Nature 427 (6971): 247–252. doi:10.1038/nature02236. PMID 14724639. 
  26. ^ "What computing can teach biology, and vice versa". The Economist. 2007-07-12. Retrieved 2010-08-08. (subscription required)