SCHOOL OF SYSTEMS AND COMPUTER ENGINEERING
David Edmundo
ROMO BUCHELI
Director of Postgraduate Office
Director of GED
Research Group
CONTACT
Information
deromob@uis.edu.co
+57 (607) 634 4000
Extension: . 1303
GENERAL
Biography
David Edmundo Romo Bucheli is a tenured professor in the School of Systems Engineering and Informatics at the Universidad Industrial de Santander (UIS) and has played a significant role as a member of the Biomedical Imaging, Vision, and Learning Laboratory (BIVL2ab) research group.
His academic background is noteworthy and includes a Ph.D. in Engineering with an emphasis on Electrical Engineering from the Universidad Nacional de Colombia, as well as a Master’s degree in Biomedical Engineering from the same institution. Additionally, he is an Electronics Engineer graduated from the Universidad Nacional de Colombia. Professor Romo Bucheli specializes in crucial areas for systems engineering and computer science, such as Data Analytics, Machine Learning, and Image Processing.
EDUCATION AND
Qualifications
-
Doctor of Engineering - Electrical Engineering
Universidad Nacional de Colombia, 2017
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Master in Biomedical Engineering
Universidad Nacional de Colombia, 2011
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Electronic Engineer
Universidad Nacional de Colombia, 2007
Director of Postgraduate Office
Director of
GED Research Group
CONTACT
Information
deromob@uis.edu.co
+57 (607) 634 4000
Extension:1303
AREAS OF
Expertise
Data Analytics
Machine learning
Image processing
OFFICE
Hours
Monday 10:00 a.m. – 12:00 m.
Wednesday 2:00 p.m. – 4:00 p.m.
Friday 8:00 a.m. – 10:00 a.m.
UIS Central Campus, Edificio Laboratorios Pesados, Escuela de Ingeniería de Sistemas e Informática
Outstanding
Works
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Computer Aided Assessment of Impact of Plastic Waste During COVID-19 Pandemic in Urban Areas of Developing Countries
Article, Chemical Engineering Transactions, 2022
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A digital cardiac disease biomarker from a generative progressive cardiac cine-MRI representation
Article, Biomedical Engineering Letters, 2022
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Reducing image variability across OCT devices with unsupervised unpaired learning for improved segmentation of retina
Article, Biomedical Optics Express, 2020