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ANTONIO CANALE

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Position

Professore Associato

Address

VIA CESARE BATTISTI, 241/243 - PADOVA

Telephone

0498274147

PRESENT POSITION
- Associate professor, Dipartimento di Scienze Statistiche, Università degli Studi di Padova. (since 03/2020)
- Abilitazione Scientifica Nazionale a professore di I fascia, settore 13/D1 (National scientific qualification for full professor in Statistics), from September 2019

PAST POSITIONS
- Assistant professor, Dipartimento di Scienze Statistiche, Università degli Studi di Padova. (from 03/2017 to 02/2020)
- Research Affiliate, de Castro Statistics Initiative, Collegio Carlo Alberto (from 02/2013 to 02/2017)
- Assistant professor, Dipartimento di Scienze ESOMAS, Università degli Studi di Torino. (from 10/2012 to 02/2017)
- Postdoctoral fellow, Dipartimento di Statistica e Matematica applicata “Diego de Castro”, Università degli Studi di Torino (from 01/2012 to 09/2012)
- Statistical Research Consultant, (from 01/2012 to 12/2012)
- Freelance Statistical Business Consultant (from 2007 to 2010)

EDUCATION
- Ph.D., Statistics, Department of Statistics, Università degli Studi di Padova (From 1/2009 to 12/2011)
- M.S., Statistics and Computer Science, Department of Statistics Università degli Studi di Padova (From 10/2006 to 07/2008)
- B.S., Statistics and Management, Department of Statistics Università degli Studi di Padova (From 10/2003 to 02/2006)

DETAILED CV IN PDF: tonycanale.github.io/canale_cv.pdf

Notices

Office hours

  • Monday from 16:00 to 17:30
    at Ufficio 155
    Contattare preventivamente il docente via email.

Publications

See https://www.research.unipd.it/simple-search?query=antonio+canale

Research Area

Bayesian nonparametrics: Models, theory and computational aspects.
Functional data analysis: Bayesian and frequentist FDA: estimation, prediction, and clustering.
Models for discrete and count data: Nonparametric mixture models for counts, probit regressions.
Flexible distributions: Statistical aspects of the Skew-normal and skew-symmetric distributions.
Applications: Business, biology and life sciences, energy markets.
Machine learning: Big data and scalable algorithms, classification techniques.