Adriana Romero Soriano

Adriana Romero is a research scientist at Meta AI Research and an adjunct professor at McGill University. The goal of her research is to develop models and algorithms that are able to learn from multi-modal and real world data, understand and reason about conceptual relations, and recognize their uncertainties, while addressing impactful problems. The playground of her research has been defined by problems which require inferring full observations from limited sensory data. Previously, she was a post-doctoral researcher at Mila, advised by Prof. Yoshua Bengio. She received her Ph.D. from Universitat de Barcelona with a thesis on assisting the training of deep neural networks, advised by Dr. Carlo Gatta.