|Carlos E. Thomaz|
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
Tel: +55 (0)11 4353 2910 (ext. 2183)
Fax: +55 (0)11 4109 5994
Email: my initials @fei.edu.br
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).
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]
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 (to appear).
J. R. B. Junior, R. A. L. Moreto, G. A. Silva, C. E. Thomaz and S. P. Gimenez. Methodology to optimize and reduce the total gate area of robust operational transconductance amplifiers by using diamond layout style for MOSFETs, Analog Integrated Circuits and Signal Processing, 14pp., November 2020.
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.
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.
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.
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., September 2020.
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, 6pp., November 2020.
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: novembro 25, 2020. Copyright of these papers, reproduced here for timely dissemination of research information, is with the respective publishers.