Isabela Albuquerque is a Research Scientist at Google DeepMind in London, UK. She holds a Ph.D. from the University of Quebec-INRS, a Bachelor's degree in Electronics from the Federal University of Pernambuco, and a Master's degree in Computer Engineering from the University of Pernambuco. Her research broadly focuses on designing more general, robust, and fair learning systems by improving their ability to generalize beyond the conditions observed during training. Her contributions include proposing domain-invariant representation learning techniques for neural networks, leveraging generative models to improve out-of-distribution generalization, and automatically debugging machine learning models. Isabela is also committed to improving diversity, equity, and inclusion in science and has participated in several initiatives from both industry and academia that aim to increase the participation of people from traditionally marginalized groups in machine learning research.