I am an assistant professor in the Department of Electrical and Computer Engineering at Concordia University in Canada. My research is focused on Pervasive Computing for Health and Healthy Aging. I am a member of the PERFORM Center, where I study ways of understanding and measuring health status and outcomes in ecological and cost-effectives ways by using wearables, sensors at home and machine learning. I also teach Software Engineering (COEN 6311)

Before coming to Concordia, I was a postdoctoral researcher at Kyushu Institute of Technology in Japan as a member of Sozolab. I worked on a project focused on how to use wearable-sensor-based activity recognition to optimize nurses work at nursing homes, specifically by reducing the time spent in documentation tasks. My research looked at ways to better use data collected in laboratory settings for activity recognition models used in real-life.

During my PhD. I studied activity recognition and routine learning at homes from non-invasive sensors embedded in objects like doors, light switches, or electric appliances, at home. The routines are described by their context to account for the fact that people usually change their routines based on context changes like day of the week, weather, presence of visitors, etc. As an invited researcher in the Informatics Laboratory of Grenoble, I had the opportunity to live in Amiqual4Home Smart Home to evaluate these ideas!

I have a Doctorate of Engineering from Universidad de Los Andes, Colombia. I received my Bachelor’s and Master Degree in Software Engineering from the same university.

Previously, I have lectured in Algorithms & Programming, Data Structures, Data Mining and Mining sensor data.