Karen Ullrich, a Research Scientist at FAIR, studies the intersection of information theory and machine learning. She discusses her PhD work, highlighting the minimum description length principle and its impact on neural network compression. Their conversation delves into the intricate ties between data compression and cognitive processes, while exploring innovative methods for addressing imaging challenges. Ullrich also shares insights on enhancing differentiability in image reconstruction and offers practical advice for new researchers navigating complex data landscapes.