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ROBERTO ROSAS ROMEROROBERTO ROSAS ROMERO
ROBERTO ROSAS ROMERO

Degrees:
Doctorado en Ingeniería Eléctrica , The University of Washington.
Maestría en Ciencias en la Especialidad en Electrónica, Instituto Nacional de Astrofísica, Óptica y Electrónica.
Licenciatura en Ingeniería en Electrónica y Comunicaciones, Universidad de las Américas Puebla.

MIEMBRO DEL SISTEMA NACIONAL DE INVESTIGADORES (SNI) Nivel 1

Areas of interest:

• Visión por Computadora • Aprendizaje Artificial • Redes Neuronales • Procesamiento de Señales • Sistemas Inteligentes
Dr. Roberto Rosas-Romero received the Ph. D. Degree in Electrical Engineering from University of Washington (Seattle, Washington, U. S. A.) in 1999. He has been full-time Professor at the Department of Electrical & Computer Engineering, Universidad de las Américas-Puebla (Puebla, México) since 2000. He also holds the position of Chair of Graduate Studies in the same department since 2012. He was a Visiting Professor at the Department of Diagnostic Radiology in Yale University (New Haven, Connecticut, U. S. A.) in 2012. He has been a Fulbright Scholar twice, as student at University of Washington in 1996-1999 and as visiting professor at Yale in 2012, respectively.

He undertook short-term visits for research and lecturing at the Department of Computer Science in University College London (London, United Kingdom) in 2018, Department of Computer Science in Durham University (Durham, United Kingdom) in 2018, CHU Sainte-Justine Research Center in Université de Montréal (Montréal, Quebec, Canada) in 2017 and Department of Sustainable Technology in Appalachian State University (Boone, North Carolina, U. S. A.) in 2010.

Dr. Rosas was recipient of funds from the Mexican Government to increase the coverage area of the Telecommunications Network in the State of Puebla in Mexico by introducing multiple wireless links (2009-2010). As a result of this project, internet services for data, voice and video are reaching isolated communities with different applications such as in education and health. He has also collaborated with faculty and students from Appalachian State University to provide a health clinic in a rural community (Puebla, México) with technology to transform solar radiation into energy for hot water and electricity (2010-2011). He has been involved with people from research groups such as the Image Processing and Analysis Group at Yale and the Vascular Imaging Lab at University of Washington.

His research interests are Signal Processing, Computer Vision, Pattern Recognition, Machine Learning and Medical Image Analysis. His research has been applied to ultrasound image segmentation, forest fire detection from video signals, micro-aneurysm detection in fundus eye images to assist in the diagnosis of diabetic retinopathy, recognition of human actions in video signals, predictive models for time series in finance (stock market), prediction of epileptic seizures based on brain waves, detection of deafness in newborn cries, alpha matte extraction from green screen images, detection of micro-calcifications on mammograms as a pre-diagnosis tool of breast cancer, transiting exo-planet identification.
  

 
 

Producción de investigación

Sección 
 
Año




Formación de recursos humanos, tesis dirigidas

2023
Detección automática de la enfermedad de Parkinson utilizando análisis de voz y análisis basado en vóxeles de resonancia magnética estructural,

2023
Detección y clasificación de quemaduras en piel humana analizando imágenes a color,

2023
Feature extraction and classification of static spiral tests to assist the detection of Parkinson’s disease,

2023
Exoplanet identification using machine learning under different noise profiles,

2022
Multiresolution analysis for transiting exoplanet identification using machine learning,



Congresos Internacionales

2020
Classification of functional near infra-red signals with machine learning for prediction of epilepsy, Tipo de participación: Ponencia Oral Nombre del congreso: 12th International Conference on Bioinformatics and Computational Biology

2019
Learning financial time series for prediction of the stock exchange market, Tipo de participación: Ponencia Oral Nombre del congreso: 34th International Conference on Computers and their Applications (CATA 2019)



Artículos de investigación

2023
Rapid screening of mayonaisse quality using computer vision and machine learning, Nombre de la revista: Journal of Food Measurement and Characterization, Volumen: 1, Número: 1, Páginas: , DOI: 10.1007/s11694-023-01814-x, ISSN: 21934126, 21934134

2023
Feature extraction and classification of static spiral tests to assist the detection of Parkinson’s disease, Nombre de la revista: Multimedia Tools and Applications, Volumen: , Número: , Páginas: , DOI: , ISSN: 13807501, 15737721

2023
Detection and classification of skin burns on color images using multi-resolution clustering and the classification of reduced feature subsets, Nombre de la revista: Multimedia Tools and Applications, Volumen: , Número: , Páginas: , DOI: 10.1007/s11042-023-17550-9, ISSN: 13807501, 15737721

2022
A new machine learning model based on the broad learning system and wavelets, Nombre de la revista: ,, Volumen: 112, Número: 104886, Páginas: , DOI: 10.1016/j.engappai.2022.104886, ISSN:

2022
Monitoring of the dehydration process of apple snacks with visual feature extraction and image processing techniques, Nombre de la revista: Applied Sciences, Volumen: 12, Número: 11269, Páginas: , DOI: 10.3390/app122111269, ISSN: 14545101

2021
Classification of PPMI MRI scans with voxel-based morphometry and machine learning to assist in the diagnosis of Parkinsons disease, Nombre de la revista: Computer Methods and Programs in Biomedicine, Volumen: 198, Número: 105793, Páginas: , DOI: 10.1016/j.cmpb.2020.105793, ISSN: 1692607, 18727565

2021
Analysis of voice as an assisting tool for detection of Parkinsons disease and its subsequent clinical interpretation, Nombre de la revista: Biomedical Signal Processing and Control, Volumen: , Número: , Páginas: , DOI: 10.1016/j.bspc.2021.102415, ISSN: 17468094

2021
Detection and classification of burnt skin via sparse representation of signals by over-redundant dictionaries, Nombre de la revista: Computers in Biology and Medicine, Volumen: 132, Número: 104310, Páginas: , DOI: 10.1016/j.compbiomed.2021.104310, ISSN: 104825, 18790534

2020
Prediction of epileptic seizures using fNIRS and machine learning, Nombre de la revista: Journal of Intelligent and Fuzzy Systems, Volumen: 38, Número: 2, Páginas: , DOI: 10.3233/JIFS-190738, ISSN: 10641246, 18758967

2020
Automatic Parkinson disease detection at early stages as pre-diagnosis tool by using classifiers and a small set of vocal features, Nombre de la revista: ,, Volumen: 40, Número: 1, Páginas: , DOI: 10.1016/j.bbe.2020.01.003, ISSN:

2019
Real-time facial expression recognition using local appearance-based descriptors, Nombre de la revista: ,, Volumen: 36, Número: 5, Páginas: , DOI: 10.3233/JIFS-179049, ISSN:

2019
Fully automatic alpha matte extraction using artificial neural networks, Nombre de la revista: Neural Computing and Applications, Volumen: , Número: , Páginas: , DOI: https://doi.org/10.1007/s00521-019-04154-4, ISSN: 9410643, 14333058

2019
Prediction of epileptic seizures with convolutional neural networks and functional near-infrared spectroscopy signals, Nombre de la revista: ,, Volumen: 111, Número: 103355, Páginas: , DOI: j.compbiomed.2019.103355, ISSN:

2019
Real-time facial expression recognition using local appearance-based descriptors, Nombre de la revista: ,, Volumen: 36, Número: 5, Páginas: , DOI: 10.3233/JIFS-179049, ISSN:

2019
Fully automatic alpha matte extraction using artificial neural networks, Nombre de la revista: ,, Volumen: 13, Número: 3, Páginas: , DOI: 10.1007/s00521-019-04154-4, ISSN:

 
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