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 is an associate editor of IEEE Latin America Transactions and 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. 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). Some recent mentoring results of this work have become a finalist project in the 2nd edition of H-INNOVA Health Innovation Award (2020/2021).

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. Such multivariate data signal and information might be an image, like a human face, a non-invasive measurement of activity in the human brain, like electroencephalography, a human visual perception of an object of interest, like eye-tracking, or even an automotive judder like the vehicle longitudinal oscillation during its clutch system engagement. For further details, please see our Research, Publications, or Image Processing Lab homepages, or contact me directly.

[Teaching, Research, Publications, FEI Face Database]


Recent works

J. B. L. Borten, M. C. M. Barros, E. S. Silva, R. C. X. Balda, T. M. Heiderich, L. P. Carlini, R. N. Orsi, C. E. Thomaz and R. Guinsburg. Pain evaluation in critically ill newborn infants: Eye tracking of adults' sight (abstract), Pediatric Academic Societies Meeting, PAS 2022, Denver, USA, 21st-25th April 2022.

F. G. Tamanaka, L. P. Carlini, T. M. Heiderich, R. C. X. Balda, M. C. M. Barros, R. Guinsburg and C. E. Thomaz. Neonatal pain assessment: A Kendall analysis between clinical and visually perceived facial features, Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 10pp., March 2022.

E. Ribeiro and C. E. Thomaz. Less acoustic features means more statistical relevance: Disclosing the clustering behavior in music stimuli, IEEE Latin America Transactions, vol. 20, no. 4, pp. 686-692, April 2022.

J. C. A. Soares, M. C. M. Barros, G. V. T. Silva, L. P. Carlini, T. M. Heideirich, R. N. Orsi, R. C. X. Balda, P. A. S. O. Silva, C. E. Thomaz and R. Guinsburg. Looking at neonatal facial features of pain: do health and non-health professionals differ?, Jornal de Pediatria, vol. 98, no. 4, pp. 406-412, July-August 2022.

[Full publications list]


Last updated: agosto 01, 2022.  Copyright of these papers, reproduced here for timely dissemination of research information, is with the respective publishers.