Stephen Muggleton
| Stephen Muggleton | |
|---|---|
 Stephen Muggleton 2010 | |
| Born | 6 December 1959 |
| 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 | |
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Website www | |
Stephen H. Muggleton FBCS, FIET, FAAAI,[6]FECCAI, FSB, FREng[7] (born 6 December 1959, son of Louis Muggleton) is Professor of Machine Learning and Head of the Computational Bioinformatics Laboratory at Imperial College London.[1][8][9][10][11][12][13]
Education
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
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) where he founded the Machine Learning Group.[15] In 1997 he took a post at the University of York and in 2001, he moved from there to Imperial College London.
Research
Muggleton's research interests[9][16] 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 2013 he holds the Syngenta/Royal Academy of Engineering Research Chair[18] Chair 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][23] 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, Cigol, Golem, Progol and Metagol [24][25] and applications — especially biological prediction tasks.
He worked on a Robot Scientist together with Ross D. King[26] that is capable of combining Inductive Logic Programming with active learning.[27] His present work concentrates on the development of Meta-Interpretive Learning,[28] a new form of Inductive Logic Programming which supports predicate invention and learning of recursive programs.
References
- 1 2 Stephen Muggleton's publications indexed by Google Scholar, a service provided by Google
- 1 2 Stephen Muggleton at the Mathematics Genealogy Project
- ↑ Moyle, Stephen Anthony (2003). An investigation into theory completion techniques in inductive logic programming (PhD thesis). University of Oxford.
- ↑ Santos, Jose Carlos Almeida (2010). Efficient learning and evaluation of complex concepts in inductive logic programming (PhD thesis). Imperial College London.
- ↑ http://www.raeng.org.uk/about/fellowship/fellowslist.htm List of Fellows of the Royal Academy of Engineering
- ↑ http://www.aaai.org/Awards/fellows-list.php
- ↑ http://www.raeng.org.uk/research/researcher/chairs/currentapp.htm Research Chairs: Current and Recently Completed at the Royal Academy of Engineering
- ↑ "Professor Stephen H. Muggleton". Academic staff list. Imperial College. Retrieved 8 August 2010.
- 1 2 Stephen Muggleton's publications indexed by the DBLP Bibliography Server at the University of Trier
- ↑ Grants awarded to Stephen Muggleton by the Engineering and Physical Sciences Research Council
- ↑ Stephen Muggleton's publications indexed by the Scopus bibliographic database, a service provided by Elsevier.
- ↑ 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.
- ↑ Stephen Muggleton from the Association for Computing Machinery (ACM) Digital Library
- ↑ Muggleton, Stephen (1987). Inductive acquisition of expert knowledge (PhD thesis). University of Edinburgh.
- ↑ Muggleton, S. (1997). "Learning from positive data" 1314: 358–376. doi:10.1007/3-540-63494-0_65.
- ↑ List of publications from Microsoft Academic Search
- ↑ Muggleton, S. (1999). "Scientific knowledge discovery using inductive logic programming". Communications of the ACM 42 (11): 42. doi:10.1145/319382.319390.
- 1 2 "Prof Stephen Muggleton". The Royal Institution of Great Britain. Retrieved 8 August 2010.
- ↑ Muggleton, S. (1991). "Inductive logic programming". New Generation Computing 8 (4): 295–318. doi:10.1007/BF03037089.
- ↑ Muggleton S.H. "Inductive Logic Programming", Academic Press, 1992.
- ↑ Muggleton, S. (1995). "Inverse entailment and progol". New Generation Computing 13 (3–4): 245–286. doi:10.1007/BF03037227.
- ↑ 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.
- ↑ 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.
- ↑ "Golem". AI Japanese Institute for Science. Retrieved 8 August 2010.
- ↑ Michalski, R.; Tecuci, G. (1994). Machine learning: a multistrategy approach (Book). Morgan Kaufmann. p. 780. ISBN 0-934613-09-5. Retrieved 8 August 2010.
- ↑ 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.
- ↑ "What computing can teach biology, and vice versa". The Economist. 2007-07-12. Retrieved 2010-08-08.(subscription required)
- ↑ Muggleton, S. H.; Lin, D.; Tamaddoni-Nezhad, A. (2015). "Meta-interpretive learning of higher-order dyadic datalog: Predicate invention revisited". Machine Learning. doi:10.1007/s10994-014-5471-y.
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