Andrew McCallum

Andrew McCallum is a research scientist at Google and maintains an appointment in the computer science department at University of Massachusetts Amherst.[3] His primary specialties are in machine learning, natural language processing, information extraction, information integration, and social network analysis.[4]

Andrew McCallum
NationalityUnited States
Alma materDartmouth College
University of Rochester[1]
Known forConditional random field
AwardsICML Test of Time (2011)
Scientific career
FieldsComputer Science, Artificial Intelligence
InstitutionsWhizBang Labs
University of Massachusetts Amherst
Google Research
Doctoral advisorDana H. Ballard[2]

Career

McCallum graduated summa cum laude from Dartmouth College in 1989. He completed his Ph.D. at University of Rochester in 1995 under the supervision of Dana H. Ballard. He was then a postdoctoral fellow, working with Sebastian Thrun and Tom M. Mitchell at Carnegie Mellon University. From 1998 to 2000 he was a Research Scientist and Research Coordinator at Justsystem Pittsburgh Research Center. From 2000 to 2002 was Vice President of Research and Development at WhizBang Labs, and Director of its Pittsburgh office. Since 2002, he worked as a professor of computer science at the University of Massachusetts Amherst. In 2020, he joined Google as a research scientist.

He was elected as a fellow of the Association for the Advancement of Artificial Intelligence[5] in 2009, and as an Association for Computing Machinery[6] in 2017. From 2014 to 2017 he was the President of International Machine Learning Society (IMLS),[7] which organizes the International Conference on Machine Learning. He is also the director of the Center for Data Science at UMass, leading a new partnership with the Chan and Zuckerberg Initiative. In 2018, the initiative made an initial grant of 5.5 million to the center, supporting research to facilitate new ways for scientists to explore and discover research articles.[8]

Main contributions

In collaboration with John Lafferty and Fernando Pereira, McCallum developed conditional random fields, first described in a paper presented at the International Conference on Machine Learning (ICML).[9] In 2011 this research paper won the ICML "Test of Time" (10-year best paper) award.[10]

McCallum has written several widely used[11] open-source software toolkits for machine learning, natural language processing and other text processing, including Rainbow,[12] Mallet (software project), and FACTORIE.[13] In addition, he was instrumental in publishing the Enron Corpus, a large collection of emails that has been used as a basis for a number of academic studies of social networking and language.

References

  1. "Bio for Andrew McCallum". Archived from the original on 4 June 2010. Retrieved 2010-05-31.
  2. "The Mathematics Genealogy Project - Andrew McCallum". Archived from the original on 6 May 2010. Retrieved 2010-05-31.
  3. "www.cs.umass.edu/faculty/faculty-directory". Archived from the original on 4 June 2010. Retrieved 2010-05-31.
  4. "Elected AAAI Fellows". Retrieved 2010-05-31.
  5. http://www.aaai.org/Awards/fellows.php
  6. "All Award Winners". awards.acm.org. Retrieved 2017-12-22.
  7. "IMLS Board". machinelearning.org. Retrieved 19 March 2015. President-Elect Andrew McCallum
  8. "UMass Center for Data Science Partners with Chan Zuckerberg Initiative to Accelerate Science and Medicine". umass.edu. Retrieved 2018-01-26.
  9. Lafferty, J.; McCallum, A.; Pereira, F.C.N. (2001). "Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data". International Conference on Machine Learning. pp. 79–87.
  10. "Test-of-Time Award ICML'11". ICML. 2011. Retrieved 15 December 2014. John D. Lafferty, Andrew McCallum, Fernando C. N. Pereira. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data.
  11. "Google Scholar search for +mccallum +rainbow +software". Retrieved 2010-05-31.
  12. "Rainbow". Archived from the original on 26 May 2010. Retrieved 2010-05-31.
  13. "FACTORIE". Retrieved 2014-05-20.


This article is issued from Wikipedia. The text is licensed under Creative Commons - Attribution - Sharealike. Additional terms may apply for the media files.