My areas of interest lie in the field of Machine Learning, Data Mining, Artificial Intelligence and Technologies, specifically in Computer Vision and Pattern Recognition. Within this field, my current research is focused on Facial Expressions Recognition and Affective Computing. I also enjoy other related fields involving Deep Learning techniques, Image Processing, Programming Languages and Photography.
I have been awarded three years in a row by the Google Research Awards for Latin America (2017, 2016, 2015), which recently changed its name to Latin America Research Awards (LARA), with my project: “Learning Dynamic Action Units for Three-dimensional Facial Expression Recognition” (It sounds better in English) guided by Prof. Pablo Arbelaez.
Currently (2017), I’m doing a PhD in Engineering at Universidad de los Andes, CO.
Abstract: We propose a novel convolutional neural network architecture to address the fine-grained recognition problem of multi-view dynamic facial action unit detection. We leverage recent gains in large-scale object recognition by formulating the task of predicting the presence or absence of a specific action unit in a still image of a human face as holistic classification. We then explore the design space of our approach by considering both shared and independent representations for separate action units, and also different CNN architectures for combining color and motion information. We then move to the novel setup of the FERA 2017 Challenge, in which we propose a multi-view extension of our approach that operates by first predicting the viewpoint from which the video was taken, and then evaluating an ensemble of action unit detectors that were trained for that specific viewpoint. Our approach is holistic, efficient, and modular, since new action units can be easily included in the overall system. Our approach significantly outperforms the baseline of the FERA 2017 Challenge, which was the previous state-of-the-art in multi-view dynamic action unit detection, with an absolute improvement of 14%.
I’m part of the Biomedical Computer Vision (BCV) group at Universidad de los Andes, Bogotá, Colombia. Our lead researcher is Prof Pablo Arbelaez.
In our group we study several medical and non-medical problems such as: Automated Detection of Lung Cancer with Artificial Intelligence, Detection of Breast Cancer using Thermographic Images, Detection of Diabetic Retinopathy using Artificial Intelligence, Action recognition in Videos, among many others.