Carlos E. Thomaz
Grupo de Processamento de Sinais e Imagens

Departamento de Engenharia Eletrica

FEI

Av. Humberto de Alencar Castelo Branco, 3972 - Assuncao

Sao Bernardo do Campo - Sao Paulo - Brazil - CEP 09850-901

Office: K5-01

Tel:  +55 (0)11 4353 2910 (ext. 2183)

Fax: +55 (0)11 4109 5994

Email: my initials @fei.edu.br

 

[How to reach FEI in Sao Bernardo do Campo, Map of the campus]


Short Biography: Carlos E. Thomaz is Professor of Statistical Pattern Recognition at the Department of Electrical Engineering, FEI University Center, Sao Paulo, Brazil. He is head of the Image Processing Lab at FEI. Carlos Thomaz received, in 1993, his B.Sc. degree in Electronic Engineering from Pontifical Catholic University of Rio de Janeiro (PUC-Rio), Rio de Janeiro, Brazil. After working for six years in industry, he obtained the M.Sc. degree in Electrical Engineering from PUC-Rio in 1999. In October 2000, he joined the Department of Computing at Imperial College London, UK, where he obtained the Ph.D. degree in Statistical Pattern Recognition in 2004. His main research interests are in Pattern Recognition, Cognitive Perception and Machine Learning and over these years he has published more than 150 journal and conference articles on these topics. Professor Thomaz was awarded, in 2012, a University of Nottingham Brazil Visiting Fellowship to work during three months in the Sir Peter Mansfield Magnetic Resonance Centre, UK. He has served as a member of organising and program committees at a number of national and international conferences. From 2015 to 2018, he was awarded a Newton Advanced Fellowship from the Royal Society, UK. Recently, in 2020, he received the Fernandes Figueira Award from the National Academy of Medicine (Brazil) for his work on human visual perception of neonatal pain developed in collaboration with researchers of the Federal University of Sao Paulo (UNIFESP).

Research Opportunities

Our research activities are mainly related to high-dimensional data analysis. We essentially investigate, propose and implement statistical and machine learning methods to extract, visualize, understand and classify patterns on signal and information (visual and cognitive) processing. Some recent projects of our research group have been developed in collaboration with the Department of Computing, Imperial College London, UK, the Department of Computer Science, National Laboratory for Scientific Computing (LNCC), Brazil, and the Department of Paediatrics, Federal University of Sao Paulo (UNIFESP), Brazil. For further details, please see our Research or Image Processing Lab homepages, or contact me directly.

[Teaching, Research, Publications, FEI Face Database]


Recent works

M. C. M. Barros, C. E. Thomaz, G. V. T. Silva, J. C. A. Soares, L. P. Carlini, T. M. Heideirich, R. N. Orsi, R. C. X. Balda, P. A. S. Orona, A. Sanudo, S. Andreoni and R. Guinsburg. Identification of pain in neonates: the adults’ visual perception of neonatal facial features, Journal of Perinatology, June 2021 (accepted).

G. V. T. Silva, M. C. M. Barros, J. C. A. Soares, L. P. Carlini, T. M. Heideirich, R. N. Orsi, R. C. X. Balda, C. E. Thomaz and R. Guinsburg. What facial features does the pediatrician look to decide that a newborn is feeling pain?, American Journal of Perinatology, May 2021 (accepted).

L. P. Carlini, L. A. Ferreira, G. A. S. Coutrin, V. V. Varoto, T. M. Heideirich, R. C. X. Balda, M. C. M. Barros, R. Guinsburg and C. E. Thomaz. Mobile convolutional neural network for neonatal pain assessment (extended abstract), Computer Vision and Pattern Recognition, CVPR 2021, LatinX in Computer Vision (LXCV) workshop, 4pp., virtual, 19th June 2021 (oral presentation).

F. G. Tamanaka, L. P. Carlini, T. M. Heideirich, R. C. X. Balda, M. C. M. Barros, R. Guinsburg and C. E. Thomaz. Neonatal pain scales study: A Kendall analysis between eye-tracking and literature facial features. In proceedings of the 21th Simposio Brasileiro de Computacao Aplicada a Saude, SBCAS 2021, 11pp., virtual, June 15th-18th 2021 (to appear).

L. F. Buzuti and C. E. Thomaz. Avaliacao de dor em expressao facial neonatal por meio de Redes Neurais Profundas. In proceedings of the 21th Simposio Brasileiro de Computacao Aplicada a Saude, SBCAS 2021, Concurso de Teses e Dissertacoes (CTD), 6pp., virtual, June 15th-18th 2021 (to appear).

C. E. Thomaz. Análisis experimental de jugadores de ajedrez utilizando medidas de clasificación de percepción visual y cognitiva, Tobii Pro Latam - Webinar (in Portuguese), 15th April 2021.

L. P. Carlini, F. G. Tamanaka, J. C. A. Soares, G. V. T. Silva, T. M. Heideirich, R. C. X. Balda, M. C. M. Barros, R. Guinsburg and C. E. Thomaz. Neonatal pain scales and human visual perception: An exploratory analysis based on facial expression recognition and eye-tracking. In proceedings of the 25th International Conference on Pattern Recognition, ICPR 2020, Workshop on Computational and Affective Intelligence in Healthcare Applications, 15pp., Milan, Italy, 10th January 2021.

R. A. L. Moreto, A. Mariano, C. E. Thomaz and S. P. Gimenez. Optimization of a low noise amplifier with two technology nodes using an interactive evolutionary approach, Analog Integrated Circuits and Signal Processing, 13pp., January 2021.

L. P. Carlini, G. F. Miranda Junior, G. A. Giraldi and C. E. Thomaz. A new method of selecting safe neighbors for the Riemannian Manifold Learning algorithm, IEEE Latin America Transactions, vol. 19, no. 1, pp. 89-97, January 2021.

R. G. M. Junior, F. T. Rocha and C. E. Thomaz. Comparison between linear and tensor models of EEG signals representation, IEEE Latin America Transactions, vol. 19, no. 1, pp. 132-137, January 2021.

[Full publications list]


Last updated: junho 10, 2021.  Copyright of these papers, reproduced here for timely dissemination of research information, is with the respective publishers.