User:Roberto Rosas Roemero

Born in the City of Puebla, México on the 29th of May, 1971. Ph. D. Degree in Electrical Engineering from University of Washington (Seattle, Washington, U. S. A.) in 1999. 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. Visiting Professor at the Department of Diagnostic Radiology in Yale University (New Haven, Connecticut, U. S. A.) in 2012. Two-time Fulbright Scholar in 1996-1999 and 2012 as a student at University of Washington and as a visiting professor at Yale, respectively. 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, Université de Montréal (Montréal, Quebec, Canada) in 2017 and Appalachian State University (Boone, North Carolina, U. S. A.) in 2010.

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). Involvement with people from research groups such as the Image Processing and Analysis Group at Yale and the Vascular Imaging Lab at University of Washington.

Research interests in Image Processing, Computer Vision, Pattern Recognition, Machine Learning, Deep Learning and Medical Image Analysis. Ongoing 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.