Department of Statistical Sciences, University of Toronto

Fang Yao

Professor

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Mailing

Address

Department of Statistical Sciences

University of Toronto 

100 St. George Street 

Toronto, ON M5S 3G3

Canada

Office

Room 6027B, Sidney Smith Hall

Phone

+1(416) 946-5970

Fax

+1(416) 978-5133 

E-Mail

fyao"AT"utstat[.]toronto[.]edu

 
Research Interest

  • Functional and longitudinal data analysis
  • Statistical modeling of high-dimensional and complex/big data
  • Nonparametric regression and smoothing methods
  • Applications involving functional, high-dimensional and complex objects, e.g., medical studies, evolutional biology, human genetics,  finance and e-commerce, chemical engineering, etc.

Publications               


Software PACE: Collection of a variety of models and methods developed for functional data analysis in Matlab


Honors & Awards


Editorial  Boards

  • Associate Editor for Journal of the American Statistical Association, 2014--present.
  • Associate Editor for The Annals of Statistics, 2013--present.

  • Associate Editor for Bernoulli Journal, 2013--present.
  • Associate Editor for Journal of Computational and Graphical Statistics, 2012--present.
  • Associate Editor for Canadian Journal of Statistics, 2010--present.
  • Completed Associate Editor terms: The Annals of Statistics (2008--2009), Electronic Journal of Statistics (2010--2012), Journal of Statistical Planning and Inference (2012--2014), Statistica Sinica (2011--2014).

Graduate Supervision

Currently recruiting PhD students who have keen interest in methodological developments for functional data, high-dimensional data, complex/big data, such as manifolds, graphs and networks. While solid theoretical and computational background are necessary for conducting high quality research, students with strong motives in pursuing academic/research careers are especially welcome to drop by and chat with me.

Teaching

  • PMU 199Y1Y (Fall 2014 & Winter 2015): A Journey to Information Behind of Numbers
  • STA4501H (Winter 2015, 2nd half): Functional Data analysis and Related Topics