Biography:Nathalie Japkowicz

Short description: Canadian computer scientist

Nathalie Japkowicz
Alma mater	McGill University University of Toronto Rutgers University
Spouse(s)	Norrin M. Ripsman
Scientific career
Fields	Machine learning, big data
Institutions	University of Ottawa American University College of Arts and Sciences
Doctoral advisor	Stephen 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

Japkowicz was born to Michel and Suzanne Japkowicz. She completed a B.Sc. at McGill University in 1988. She earned an M.Sc. from the University of Toronto in 1990. She completed a Ph.D. at Rutgers University in 1999. Her dissertation was titled Concept-learning in the absence of counter-examples: an autoassociation-based approach to classification. Andrew Gelsey was her interim doctoral advisor from January to August 1995. Stephen José Hanson and Casimir Alexander Kulikowski were her doctoral advisors. Japkowicz dedicated her dissertation to her parents and husband, Norrin M. Ripsman.

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

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

Selected works

• Gao, Yong, ed (2009) (in en). 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. 5549. Berlin, Heidelberg: Springer Berlin Heidelberg. doi:10.1007/978-3-642-01818-3. ISBN 978-3-642-01817-6. 
• 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. 
• Japkowicz, Nathalie, ed (2015) (in en). Discovery Science: 18th International Conference, DS 2015, Banff, AB, Canada, October 4–6, 2015. Proceedings. Lecture Notes in Computer Science. 9356. Cham: Springer International Publishing. doi:10.1007/978-3-319-24282-8. ISBN 978-3-319-24281-1. 
• Japkowicz, Nathalie, ed (2016) (in en). Big Data Analysis: New Algorithms for a New Society. Studies in Big Data. 16. Cham: Springer International Publishing. doi:10.1007/978-3-319-26989-4. ISBN 978-3-319-26987-0. 
• Ceci, Michelangelo, ed (2018). Foundations of Intelligent Systems: 24th International Symposium, ISMIS 2018, Limassol, Cyprus, October 29–31, 2018, Proceedings. Lecture Notes in Computer Science. 11177. Cham: Springer International Publishing. doi:10.1007/978-3-030-01851-1. ISBN 978-3-030-01850-4. 

See also

• Autoencoder
• Citation graph
• One-class classification
• Women in computing in Canada