Geoff Webb Explained

Geoffrey I. Webb
Citizenship:Australia
Fields:Data Science
Computer Science
Artificial Intelligence
Machine Learning
Computational Biology
Workplaces:Monash University Department of Data Science and Artificial Intelligence
Notable Students:Ying Yang
Jiangning Song
Chang Wei Tan
Awards:Inaugural Eureka Prize for Excellence in Data Science, 2017
IEEE Fellow
IEEE International Conference on Data Mining 10-year Highest Impact Award, 2023
Pacific-Asia Conference on Knowledge Discovery and Data Mining Distinguished Research Contributions Award, 2022
Australian Computer Society ICT Researcher of the Year Award 2016
IEEE International Conference on Data Mining Outstanding Service Award, 2013
Australian Research Council Outstanding Researcher Award, 2014

Geoffrey I. Webb (also known as Geoff Webb) is Professor in the Department of Data Science and Artificial Intelligence at Monash University, founder and director of Data Mining software development and consultancy company G. I. Webb and Associates,[1] and former editor-in-chief of the journal Data Mining and Knowledge Discovery.[2] Before joining Monash University he was on the faculty at Griffith University from 1986 to 1988 and then at Deakin University from 1988 to 2002.

Webb has published more than 300 scientific papers in the fields of machine learning, data science, data mining, data analytics, time series analytics, big data, bioinformatics and user modeling. He is an editor of the Encyclopedia of Machine Learning.[3]

Webb created the Averaged One-Dependence Estimators (AODE) machine learning algorithm[4] and its generalization Averaged N-Dependence Estimators (ANDE)[5] and has worked extensively on statistically sound association rule learning.[6] [7] [8] [9] His early work included advocating the use of machine learning to create black box user models;[10] interactive machine learning;[11] [12] decision tree grafting;[13] and one of the first approaches to association rule learning using minimum support and confidence to find the rules for the first associative classifier, FBM.[14] He has developed multiple novel approaches to time series classification.[15] [16] [17] He has worked on diverse problems including concept drift,[18] scalable learning of graphical models,[19] human in the loop machine learning,[20] computational protein biology.[21]

Webb's awards include inaugural Eureka Prize for Excellence in Data Science, 2017,[22] IEEE Fellow,[23] IEEE International Conference on Data Mining 10-year Highest Impact Award, 2023,[24] Pacific-Asia Conference on Knowledge Discovery and Data Mining Distinguished Research Contributions Award, 2022,[25] Australian Computer Society ICT Researcher of the Year Award 2016,[26] the IEEE International Conference on Data Mining Outstanding Service Award, 2013[27] an Australian Research Council Outstanding Researcher Award, 2014[28] and multiple Australian Research Council Discovery Grants.[29] He has thrice been recognised by The Australian Research Magazine as Australia's leading Bioinformatics and Computational Biology researcher[30] [31] [32] as well as Australia's leading Data Mining and Analysis researcher.[33]

Webb is a foundation member of the editorial advisory board of the journal Statistical Analysis and Data Mining.[34] He has served on the Editorial Boards of the journals Machine Learning, ACM Transactions on Knowledge Discovery in Data, User Modeling and UserAdapted Interaction, and Knowledge and Information Systems.

Webb was elected to the ACM Special Interest Group on Knowledge Discovery and Data Mining Executive Committee in 2017.[35]

External links

Notes and References

  1. http://www.giwebb.com "G. I. Webb and Associates"
  2. https://www.springer.com/computer/database+management+%26+information+retrieval/journal/10618 "Data Mining and Knowledge Discovery Journal"
  3. https://www.springer.com/computer/ai/book/978-0-387-30768-8 "Encyclopedia of Machine Learning"
  4. Webb. Geoffrey. J. Boughton . Z. Wang . Not So Naive Bayes: Aggregating One-Dependence Estimators. Machine Learning. 2005. 58. 1. 5–24. 10.1007/s10994-005-4258-6. 10.1.1.3.7847. 13148847.
  5. Webb. Geoffrey . J. Boughton . F. Zheng . K.M. Ting . H. Salem. Learning by extrapolation from marginal to full-multivariate probability distributions: Decreasingly naive Bayesian classification. Machine Learning. 2012. 86. 2. 233–272. 10.1007/s10994-011-5263-6. free.
  6. Webb . Geoffrey . Discovering Significant Patterns . Machine Learning . 2007 . 68 . 1 . 1–33 . 10.1007/s10994-007-5006-x . free .
  7. Webb. Geoffrey. Layered Critical Values: A Powerful Direct-Adjustment Approach to Discovering Significant Patterns. Machine Learning. 2008. 71. 2–3. 307–323. 10.1007/s10994-008-5046-x. free.
  8. Webb. Geoffrey . Self-sufficient itemsets: An approach to screening potentially interesting associations between items . ACM Transactions on Knowledge Discovery from Data . 2010. 4. 3:1–3:20. 10.1145/1644873.1644876. 774593.
  9. Webb. Geoffrey. Filtered-top-k Association Discovery. WIREs Data Mining and Knowledge Discovery. 2011. 1. 3. 183–192. 10.1002/widm.28. 10.1.1.228.2541. 14839879.
  10. Webb. Geoffrey. M. Kuzmycz. Feature based modelling: a methodology for producing coherent, consistent, dynamically changing models of agents' competencies. User Modeling and User-Adapted Interaction. 1996. 5. 2. 117–150. 10.1007/BF01099758. 12003265.
  11. Webb. Geoffrey. Integrating Machine Learning With Knowledge Acquisition Through Direct Interaction With Domain Experts. Knowledge-Based Systems. 1996. 9. 4. 253–266. 10.1016/0950-7051(96)01033-7. 10.1.1.228.3037.
  12. Webb. Geoffrey. J. Wells. Z. Zheng. An Experimental Evaluation of Integrating Machine Learning with Knowledge Acquisition. Machine Learning. 1999. 35. 1. 5–14. 10.1023/A:1007504102006. free.
  13. Webb. Geoffrey. Further Experimental Evidence Against The Utility Of Occam's Razor. Journal of Artificial Intelligence Research. 1996. 4. 397–417. 10.1613/jair.228. 6088084 . free.
  14. Webb. Geoffrey. A Machine Learning Approach to Student Modelling. Proceedings of the Third Australian Joint Conference on Artificial Intelligence (AI 89). 1989. 195–205.
  15. Dempster. Angus. F. Petitjean . G. Webb . ROCKET: Exceptionally fast and accurate time series classification using random convolutional kernels. Data Mining and Knowledge Discovery. 2020. 34. 5. 1454–1495. 10.1007/s10618-020-00701-z. 1910.13051 . 204949593 .
  16. Fawaz. Hassan. B. Lucas . G. Forestier . C. Pelletier. D. Schmidt. J. Weber. G. Webb. L. Idoumghar. P. Muller. F. Petitjean. InceptionTime: Finding AlexNet for Time Series Classification. Data Mining and Knowledge Discovery. 2020. 34. 5. 1936–1962. 10.1007/s10618-020-00710-y. 1909.04939 . 202572652 .
  17. Shifaz. Ahmed. C. Pelletier. F. Petitjean . G. Webb . TS-CHIEF: A Scalable and Accurate Forest Algorithm for Time Series Classification. Data Mining and Knowledge Discovery. 2020. 34. 3. 742–775. 10.1007/s10618-020-00679-8. 1906.10329 . 195584256 .
  18. http://i.giwebb.com/research/concept-drift/ "Concept Drift: Learning From Non-Stationary Distributions"
  19. http://i.giwebb.com/research/scalable-graphical-modeling/ "Scalable Graphical Modeling"
  20. http://i.giwebb.com/research/interactive-machine-learning/ "Interactive machine learning and data analytics"
  21. http://i.giwebb.com/research/computational-biology/ "Computational Biology"
  22. http://australianmuseum.net.au/2017-eureka-prizes-winners "Eureka Prize Winners 2017"
  23. https://web.archive.org/web/20141207023338/http://www.ieee.org/2015_updated_fellows.pdf "IEEE Fellows 2015"
  24. https://icdm.zhonghuapu.com/Awards/Awards.shtml "IEEE Data Mining Awards"
  25. http://pakdd.net/awards.html "PAKDD 2022 Awards"
  26. http://reimagination16.acs.org.au/digital-disruptors-awards/ ACS Digital Disruptors Awards Winners 2016
  27. Web site: "IEEE Data Mining Awards" . 2013-10-20 . https://web.archive.org/web/20170818204759/http://www.cs.uvm.edu/~icdm/Awards.shtml . 2017-08-18 . dead .
  28. http://arc.gov.au/pdf/DP14/DP14_Listing_by_State_and_Org.pdf Discovery Projects Funding Outcomes for Projects Commencing in 2014
  29. Web site: "Discovery Projects Funding Outcomes" . 2013-10-20 . https://web.archive.org/web/20131023055513/http://www.arc.gov.au/ncgp/dp/dp_outcomes.htm . 2013-10-23 . dead .
  30. News: Deep Dive Into Research . 10 November 2022 . 2021 . The Australian . 10 November 2021.
  31. News: Our top researchers in Field Leaders Engineering & Computer Science . 10 November 2022 . 2023 . The Australian . 9 November 2022.
  32. News: Engineering & Computer Science Australia's Research Field Leaders . 21 November 2023 . 2024 . The Australian . 21 November 2023.
  33. News: Engineering & Computer Science Australia's Research Field Leaders . 21 November 2023 . 2024 . The Australian . 21 November 2023.
  34. http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1932-1872/homepage/EditorialBoard.html Statistical Analysis and Data Mining Editorial Board
  35. http://www.kdd.org/about About SIGKDD

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