Carlos E. Thomaz
Grupo de Processamento de Sinais e Imagens

Departamento de Engenharia Eletrica


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


[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 140 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, Talks, Activities, FEI Face Database, News]

Recent works

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. Computational framework to classify neonatal facial expression of pain: A real world mobile application, IEEE Seasonal School on Digital Processing of Visual Signals and Applications (DPVSA), Rio Grande do Sul, Brazil, October 19th-21th 2020 (to appear).

W. Pires, R. N. Orsi and C. E. Thomaz. A influencia de imagens de carater emocional na dilatacao pupilar e na tomada de decisao economica intertemporal. In proceedings of the VII Encontro Brasileiro de Economia e Financas Comportamentais, 23pp., Sao Paulo, Sao Paulo, Brazil, November 9th-10th 2020 (to appear).

L. R. S. Junior and C. E. Thomaz. Cognitive metrics to classify chess players' expertise based on EEG and eye movement signals, October 2020 (submitted).

F. G. Tamanaka, T. M. Heideirich, M. C. M. Barros, R. C. X. Balda, R. Guinsburg and C. E. Thomaz. Escalas de dor em neonatos: Uma revisao das caracteristicas faciais relevantes, October 2020 (submitted).

T. A. Filisbino, G. A. Giraldi and C. E. Thomaz. Support vector machine ensembles for discriminant analysis for ranking principal components, Multimedia Tools and Applications, 37pp., July 2020.

P. A. S. Orona, D. A. D. Fabbro, T. M. Heiderich, M. C. M. Barros, R. C. X. Balda, R. Guinsburg and C. E. Thomaz. Interpretacao e reconhecimento de padroes para avaliacao de dor em imagens faciais de recem-nascidos. In proceedings of the 20th Simposio Brasileiro de Computacao Aplicada a Saude, SBCAS 2020, pp. 285-296, Salvador, Bahia, Brazil, September 15th-18th 2020.

L. F. Buzuti, T. M. Heiderich, M. C. M. Barros, R. Guinsburg and C. E. Thomaz. Neonatal pain assessment from facial expression using Deep Neural Networks. In proceedings of the XVI Workshop de Visao Computacional, WVC 2020, pp. 87-92, Uberlandia, Minas Gerais, Brazil, October 7th-8th 2020.

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, 8pp., accepted in June 2020 (video-abstract, in portuguese).

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, 7pp., August 2020 (accepted).

M. C. M. Barros, C. E. Thomaz, G. V. T. Silva, J. C. A. Soares, L. P. Carlini, T. M. Heiderich, R. N. Orsi, R. C. X. Balda, P. A. S. O. Silva, A. Sanudo, S. Andreoni and R. Guinsburg. Identification of pain in neonates: the adults' visual perception of neonatal facial features, 23pp., September 2020 (in revision by the authors).

C. E. Thomaz. Face-space concept revisited: A multilinear subspace learning of priori-driven physiognomic dimensions, January 2020 (in preparation).

[Full publications list]

Last updated: outubro 16, 2020.  Copyright of these papers, reproduced here for timely dissemination of research information, is with the respective publishers.