Alessandro Lameiras Koerich
Alessandro Lameiras Koerich
B.Ing (UFSC, Brésil), M.Sc. (UNICAMP, Brésil), Ph.D. (ÉTS)
Professeur
Département de génie logiciel et des TI

I have been teaching for more than two decades in several universities: Federal Technological University of Paraná (UTFPR - Brazil) [1997-1998], Pontifical Catholic University of Paraná (PUCPR - Brazil) [2002-2015], University of Curitiba (UniCuritiba - Brazil) [2003-2005], Federal University of Paraná (UFPR - Brazi) [2009-2015].
 

Winter 2016:

Summer 2015:

  • GTI770 - Intelligent Systems and Machine Learning (ÉTS) (45 undergraduate students of Software Engineering and IT Engineering): Introductory course that gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as feature extraction and classification and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, ensembles of classifiers and rejection. The course gives the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and when they work.

Winter/Spring 2014:

Summer/Fall 2014:

 Winter/Spring 2013:

  • TE826 - Machine Learning (UFPR-Brazil) (14 graduate students)
  • Circuit Analysis II (PUCPR-Brazil) (50 undergraduate students)
  • TE216 - Lab of Electronics II (UFPR-Brazil)(50 undergraduate students)
  • TE256 - Reliability of Electronic Systems (UFPR-Brazil)(30 undergraduate students): Advanced level class emphasizing the reliability of electronic components and systems.

Summer/Fall 2013:

Winter/Spring 2012:

  • TE826 - Machine Learning (UFPR-Brazil) (3 graduate students)
  • Circuit Analysis II (PUCPR-Brazil) (50 undergraduate students): Fundamental level class emphasizing the analysis of AC circuits.
  • TE216 - Lab of Electronics II (UFPR-Brazil) (50 undergraduate students)

Summer/Fall 2012:

  • Machine Learning (PUCPR-Brazil) (12 graduate students)
  • Circuit Analysis I (PUCPR-Brazil)(50 undergraduate students): Fundamental level class emphasizing the analysis of CC circuits.
  • TE215 - Lab of Electronics I (UFPR-Brazil) (50 undergraduate students)
  • TE214 - Fundamentals of Electronics (UFPR-Brazil) (60 undergraduate students)

Winter/Spring 2011:

  • TE826 - Machine Learning (UFPR-Brazil) (3 graduate students)
  • TE216 - Lab of Electronics II (UFPR-Brazil)(50 undergraduate students)
  • Law and Legislation for Engineers (PUCPR-Brazil) (25 undergraduate students)
  • Pattern Recognition (PUCPR-Brazil) (22 undergraduate students)

Summer/Fall 2011:

  • Machine Learning (PUCPR-Brazil) (6 graduate students)
  • TE215 - Lab of Electronics I (UFPR-Brazil)(50 undergraduate students)
  • TE214 - Fundamentals of Electronics (UFPR-Brazil)(60 undergraduate students)
  • Law and Legislation for Engineers (PUCPR-Brazil) (25 undergraduate students)
  • Pattern Recognition (PUCPR-Brazil) (25 undergraduate students)

Winter/Spring 2010:

  • TE826 - Machine Learning (UFPR-Brazil)(3 graduate students)
  • TE216 - Lab of Electronics II (UFPR-Brazil)(50 undergraduate students): Fundamental level class emphasizing the experiments with AC circuits using BJT and MOSFET transistors.
  • Law and Legislation for Engineers (PUCPR-Brazil) (28 undergraduate students)
  • Pattern Recognition (PUCPR-Brazil) (12 undergraduate students)

Summer/Fall 2010:

Winter/Spring 2009:

Summer/Fall 2009:

  • Machine Learning (PUCPR-Brazil) (8 graduate students)
  • Analysis and Design of Algorithms (PUCPR-Brazil) (60 undergraduate students)
  • Law and Legislation for Engineers (PUCPR-Brazil) (22 undergraduate students)
  • Pattern Recognition (PUCPR-Brazil) (12 undergraduate students)

Winter/Spring 2008:

  • Pattern Recognition (PUCPR-Brazil) (25 undergraduate students): Advanced course to senior students that gives an overview of many concepts, techniques, and algorithms in pattern recognition.
  • Law and Legislation for Engineers (PUCPR-Brazil) (25 undergraduate students): Introductory course to senior students that gives an overview of the legislation related to the profession of engineering.
  • Analysis and Design of Algorithms (PUCPR-Brazil) (32 undergraduate students)
  • Artificial Intelligence (PUCPR-Brazil) (23 undergraduate students)

Summer/Fall 2008:

Winter/Spring 2007:

Summer/Fall 2007:

Winter/Spring 2006:


Summer/Fall 2006:

Winter/Spring 2005:

Summer/Fall 2005:

  • Machine Learning (PUCPR-Brazil) (12 graduate students): Introductory course that gives an overview of many concepts, techniques, and algorithms in machine learning, beginning with topics such as feature extraction and classification and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, ensembles of classifiers and rejection. The course gives the basic ideas and intuition behind modern machine learning methods as well as a bit more formal understanding of how, why, and when they work.
  • Analysis and Design of Algorithms (PUCPR-Brazil)(42 undergraduate students)
  • Parallel Programming (PUCPR-Brazil) (23 undergraduate students)
  • Multimedia (UniCuritiba-Brazil) (50 undergraduate students).

Winter/Spring 2004:

Summer/Fall 2004:

  • Artificial Intelligence (PUCPR-Brazil) (12 graduate students)
  • Analysis and Design of Algorithms (PUCPR-Brazil)(35 undergraduate students)
  • Parallel Programming (PUCPR-Brazil) (27 undergraduate students)
  • Multimedia (UniCuritiba-Brazil) (50 undergraduate students).

Winter/Spring 2003:

Summer/Fall 2003:

  • Artificial Intelligence (PUCPR-Brazil) (15 graduate students): Introductory course that gives an overview of many concepts, techniques, and algorithms in artificial intelligence, beginning with topics such as searching algorithms and classification and ending up with more recent topics such as boosting, support vector machines, hidden Markov models, ensembles of classifiers and rejection. The course gives the basic ideas and intuition behind artificial intelligence methods as well as a bit more formal understanding of how, why, and when they work.
  • Analysis and Design of Algorithms (PUCPR-Brazil) (60 undergraduate students): Introductory course on fundamentals of analysis and design of algorithms to sophomore students.
  • Parallel Programming (PUCPR-Brazil) (30 undergraduate students): Advanced course to senior students that gives an overview of many concepts, techniques, and algorithms for multicore and parallel computing, including practical activities with computer clusters in laboratory.
  • Multimedia (UniCuritiba-Brazil) (50 undergraduate students).


Me joindre

Bureau : A-4487
Téléphone : 514 396-8574
Télécopieur: 514 396-8405

alessandro.lameiras-koerich@etsmtl.ca

Nouvelles

Paper accepted at the IEEE SMC 2017
Multiple Classifier System for Plant Leaf Recognition 
Paper accepted at the IEEE ICASSP 2017
Two-Stage Facial Age Prediction using Group-Specific Features 
Paper accepted at the INTERSPEECH 2016
Native Language Detection using the I-Vector Framework 
Paper accepted at the IEEE IJCNN 2016
Facial Expression Recognition Using a Pairwise Feature Selection 
Paper accepted at Pattern Recognition
A Flexible Hierarchical Approach For Facial Age Estimation 
Paper accepted at the ACM Multimedia 2015
Paper accepted for the AV+EC 2015 Challenge at the ACM Multimedia 2015. 
Paper published at Expert Systems
PKLot – A robust dataset for parking lot classification.