Issam Laradji is a research scientist at ServiceNow Research who focuses on methods that minimize the amount of labels required to efficiently train machine learning models. He completed his postdoc at McGill’s Graphics lab and completed his PhD at the Machine Learning lab of University of British Columbia. His current topics of interest are natural language processing, computer vision (both 2D and 3D), and optimization. On the side, he continuously works on Haven-AI, a toolkit to help people build end-to-end deep learning methods and manage large-scale experiments.