I am a Research Officer at the National Research Council of Canada (NRC). At the NRC, my work focuses on the developement of AI for design problems. In this context, my researching aims to understand and improve the ability of AI methods to learn from limited and costly data. Amongst other things, I am actively working on deep learning from limited and imbalanced data and cost-sensitive reinforcement leanring.
Previously, I spent 3 months at Dalhousie University funded by the Donald Hill Postdoctoral Fellowship. During that time, I collaborated on research related to class imbalance and learning from rare cases with Dr. Luis Torgo. From 2016 - 2018, I held a Postdoctoral Fellowship with the Alberta Machine Intelligence Institute(AMII) at the University of Alberta, under Dr. Osmar Zaiane. In addition to researching class imbalance and anomaly detection, I collaborated with industrial and medical partners to solve practical problems in treatment recommendation, knowledge discovery and failure prediction. I also co-organized the AI Seminar at the University of Alberta.
I completed my PhD in Computer Science at the University of Ottawa, under Dr. Nathalie Japkowicz and Christopher Drummond in 2016. My research focused synthetic oversampling with autoencoders and manifold learning techniques. In addition, I worked on applications involving one-class classification. I completed my Masters in Computer Science at Carleton University under Dr. John Oommen, where my research focused on modelling and predicting stochastically episodic events. My thesis passed with distinction.
I have published and present papers at major conferences around the world, and received two 'best paper' awards. My research has been published in many reviewed journal of international esteem, such as Machine Learning and Expert Systems with Applications. In addition, I have co-author two book chapters, one AI for Good and the other on emerging trends in machine learning. A complete list of my publications can be found here. I have also been invited to teach as a guest lecturer for graduate level courses in machine learning and data mining at both the University of Ottawa and the University of Alberta, as well as for an undergraduate programming courses in Python and Java. For a complete list of courses that I have taught, please visit this page.
In 2012, I was a visiting researcher at Centro de Informatica, Universidade Federal de Pernambuco (UFPE), and in 2015, I was a visiting researcher at the University of Telca, Chile.
During the course of my academic career, I have been on the program committees of numerous major conferences and peer review for many journals in computer science and health science. These including, but are not limited to, NeurIPS, IJCAI, AAAI, Information Science, Neurocomputing, Expert Systems with Applications, and BMC Medical Informatics And Decision Making. Furthermore, I reviewed for the NSERC College and Community Innovation Grant and multiple Chilean national science grant.
I co-chaired the Graduate Student Symposium at the Canadian Artificial Conference in 2016 and 2018, and co-organized workshops on class imbalance and deep learning at ICLR 2021 and SIGKDD 2022.
My full curriculum vitae can be obtained from here.