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Nathalie Japkowicz

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Nathalie Japkowicz
Alma materMcGill University
University of Toronto
Rutgers University
Scientific career
FieldsMachine learning, big data
InstitutionsUniversity of Ottawa
American University College of Arts and Sciences
Doctoral advisorStephen José Hanson, Casimir Alexander Kulikowski

Nathalie Japkowicz is a Canadian computer scientist specializing in machine learning. She is a professor and department chair of computer science at the American University College of Arts and Sciences.

Life

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Nathalie Japkowicz completed a B.Sc. at McGill University in 1988.[1] She earned an M.Sc. from the University of Toronto in 1990.[1] She completed a Ph.D. at Rutgers University in 1999.[1] Her dissertation was titled Concept-learning in the absence of counter-examples: an autoassociation-based approach to classification.[2] Stephen José Hanson and Casimir Alexander Kulikowski were her doctoral advisors.[2]

Japkowicz worked at the University of Ottawa in the school of electrical engineering and computer science.[1] She was the lead of its laboratory for research on machine learning for defense security.[1] From 2003 to 2005, Japkowicz was the secretary of the Canadian Artificial Intelligence Association (CAIAC).[3] She was CAIAC vice president from 2009 to 2014 and president from 2013 to 2015, and part-president from 2015 to 2017.[3][4]

Japkowicz is a professor and department chair of computer science at the American University College of Arts and Sciences.[1] She researches artificial intelligence, machine learning, data mining, and big data analysis.[5]

Selected works

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  • Gao, Yong; Japkowicz, Nathalie, eds. (2009). Advances in Artificial Intelligence: 22nd Canadian Conference on Artificial Intelligence, Canadian AI 2009 Kelowna, Canada, May 25–27, 2009 Proceedings. Lecture Notes in Computer Science. Vol. 5549. Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-01818-3. ISBN 978-3-642-01817-6. S2CID 27083226.
  • Japkowicz, Nathalie; Shah, Mohak (2011). Evaluating Learning Algorithms: A Classification Perspective (1 ed.). Cambridge University Press. doi:10.1017/cbo9780511921803. ISBN 978-0-511-92180-3.[6]
  • Japkowicz, Nathalie; Matwin, Stan, eds. (2015). Discovery Science: 18th International Conference, DS 2015, Banff, AB, Canada, October 4–6, 2015. Proceedings. Lecture Notes in Computer Science. Vol. 9356. Cham: Springer International Publishing. doi:10.1007/978-3-319-24282-8. ISBN 978-3-319-24281-1. S2CID 1302223.
  • Japkowicz, Nathalie; Stefanowski, Jerzy, eds. (2016). Big Data Analysis: New Algorithms for a New Society. Studies in Big Data. Vol. 16. Cham: Springer International Publishing. doi:10.1007/978-3-319-26989-4. ISBN 978-3-319-26987-0.
  • Ceci, Michelangelo; Japkowicz, Nathalie; Liu, Jiming; Papadopoulos, George A.; Raś, Zbigniew W., eds. (2018). Foundations of Intelligent Systems: 24th International Symposium, ISMIS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings. Lecture Notes in Computer Science. Vol. 11177. Cham: Springer International Publishing. doi:10.1007/978-3-030-01851-1. ISBN 978-3-030-01850-4. S2CID 53038780.

See also

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References

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  1. ^ a b c d e f "Professor and Department Chair, Computer Science". American University. Retrieved 2023-04-29.
  2. ^ a b Japkowicz, Nathalie (1999). Concept-learning in the absence of counter-examples: an autoassociation-based approach to classification (Ph.D. thesis). Rutgers University. OCLC 78440062.
  3. ^ a b "Dr. Nathalie Japkowicz | CAIAC". www.caiac.ca. Retrieved 2023-04-29.
  4. ^ "Homepage of Nathalie Japkowicz". www.site.uottawa.ca. Retrieved 2023-04-29.
  5. ^ "Homepage of Nathalie Japkowicz". fs2.american.edu. Retrieved 2023-04-29.
  6. ^ Ghosh, Subir (2013). "Review of Evaluating Learning Algorithms: A Classification Perspective". Technometrics. 55 (2): 252–253. ISSN 0040-1706. JSTOR 24587142.
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