Moacir A. Ponti

Associate Professor of Computer Science

Institute of Mathematical and Computer Sciences, Universidade de São Paulo - USP at São Carlos, Brazil

Main Research fields: Machine Learning/Representation Learning; Signal, Image and Video Processing

In search for fair and explainable ways to apply machine learning and computer vision to improve people's life.


Recent/highlighted papers (see Publication for more details):

Check out my Book on Machine Learning (Theory and Practice), details below!

I am recipient of a Google Latin America Research Award (2017-2018).

At USP I have 10 years experience in teaching, as a principal investigator of many research projects and grants, and leadership, by chairing a Science Outreach committee, bridging the gap between acacemia, individuals, organizations and industry.

Previous experiences/education:
Academic visitor (2016-2017); Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey, UK.
PhD (2008) and MSc (2004) at the
Universidade Federal de São Carlos (UFSCar), Brazil.
PhD internship (2007) at
IEETA, Universidade de Aveiro, Portugal.

CV: Lattes Platform CV (in Portuguese) -- 4-page CV in English [pdf]


External sites (papers, code and citations):
Github - GoogleCitations- SCOPUS - DBLP - Researcher-ID - ORCID - Linkedin

Address:
Instituto de Ciências Matemáticas e de Computação
Universidade de São Paulo - Campus de São Carlos
P.O. Box 668 / 13566-590 / São Carlos, SP, Brasil

Machine Learning: A Practical Approach on the Statistical Learning Theory

Rodrigo F. Mello . Moacir A. Ponti

Presents the Statistical Learning Theory in a detailed and easy to understand way, by using practical examples, algorithms and source codes. It can be used as a textbook in graduation or undergraduation courses, for self-learners, or as reference with respect to the main theoretical concepts of Machine Learning. Fundamental concepts of Linear Algebra and Optimization applied to Machine Learning are provided, as well as source codes in R, making the book as self-contained as possible.