Biography
I have performed research and development activities in aspects related to data science and machine learning for health-care, security, and business applications during more than eight years. My expertise spans machine learning, deep learning, and analysis of time-series such as audio, natural language, and those coming from a variety of sensors to model especially human behavior and consumer habits. Thanks to my interdisciplinary background, I have successful record of accomplishments in both industry and academia. My background involves the application of machine learning methods to analyze signals such as speech, handwriting, gait, energy consumption, and natural language to monitor and to detect different human traits like emotions, personality, health-states, consumer habits, among others. I have supervised as well several projects regarding the designing and development of machine learning technologies for different applications such as biometric identification, health-care modeling, and business document analysis, using information from speech, text documents, facial expression, keystroke dynamics, among others. I am an expert on several frameworks including the standard SciPy Stack (Numpy, SciPy, Pandas, Scikit-Learn, Matplotlib), Tensorflow, Pytorch, Kaldi, Spacy, among others designed for machine learning, natural language processing, and time-series modeling.
Interests
- Signal Processing
- Machine Learning and Deep Learning
- Signal Processing
- Natural language processing
Education
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PhD in Computer science, 2018 - currently
Friedrich Alexander University
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PhD in Computer science and Electrical Engineering, 2018 - currently
University of Antioquia
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MEng in Telecommunications Engineering, 2016
University of Antioquia
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BSc in Electrical Engineering, 2013
University of Antioquia
