Hi! My name is Laura and I am a PhD student working on language and reinforcement learning in the UCL DARK lab. I'm (very broadly) interested in generalization in machine learning. Finding failure modes of contemporary deep learning methods, and trying to improve them.
Currently - PhD candidate at University College London supervised by Tim Rocktäschel and Ed Grefenstette
Assistant Research Scientist at New York University in Brenden Lake's Human and Machine Learning Lab
Master Thesis Intern at Google in the Perception team working on human perception of audio
Research Intern at Facebook Artificial Intelligence Research (FAIR) working on systematic generalization in language
Software Engineering Intern at Google in the Assistant team working on automatic text simplification and partly autoregressive transformers
Teaching Assistant at University of Amsterdam (UvA) for courses like Data Processing and Natural Language Processing
Masters in AI at University of Amsterdam (UvA), graduated cum laude.
November 2021 -- I wrote a blogpost on Learning in High Dimension Always Amounts to Extrapolation, find it here.
December 2020 -- I'll present gSCAN at NeurIPS on Thursday December 10th at 9AM PST in poster session 6. Find the version of the poster with a bit more textual explanation than the one in the proceedings here.
September 2020 -- GroundedSCAN got accepted to NeurIPS 2020! The camera-ready version is now available on arXiv.
Ruis, L. and Lake, B. M. (2022). Improving Systematic Generalization Through Modularity and Augmentation. In Proceedings of the 44th Annual Conference of the Cognitive Science Society.
Ruis, L., Andreas, J., Baroni, M. Bouchacourt, D., and Lake, B. M. (2020). A Benchmark for Systematic Generalization in Grounded Language Understanding. Advances in Neural Information Processing Systems 33.
Ruis, L., Stern, M., Proskurnia, J., and Chan, W. (2019). Insertion-Deletion Transformer. Extended Abstract in EMNLP: Workshop of Neural Generation and Translation.