Photo credit: Alina l'Ami
Hi all! I'm a PhD student interested in understanding and designing more robust, theoretically grounded machine learning algorithms. I'm supervised by Yarin Gal, and a member of the AIMS CDT and OATML lab. My DPhil is jointly funded by DeepMind and EPSRC.
I hold a BSc in Econometrics and Operations Research from Erasmus University Rotterdam, and two MScs in the fields of Statistics and Computer Science from the University of Oxford. I'm curious about a wide range of topics, generally falling under the areas of statistics, machine learning, and optimization.
Since the age of eight, I've been passionate about playing chess. Originally, chess was simply a family activity, but incipiently I became enamored with the game - I love the interplay between creativity, sharp analytical skills, and psychology. At the age of twelve, I played my first World Youth Championship and by the age of fourteen, became the youngest ever member of the Dutch Olympic Chess team. During my chess career, I set 14 national records; highlights include becoming the youngest Women's International Master (beating the previous record by four years), threefold medalist at European and World Youth Championships, and undefeated Dutch Champion. In 2014, we, the Dutch national women's team, founded ChessQueens to improve gender equality in chess in the Netherlands by supporting female chess players.
Uncertainty-Aware Counterfactual Explanations for Medical Diagnosis. Lisa Schut, Oscar Key, Rory McGrath, Luca Costabello, Bogdan Sacaleanu, Medb Corcoran, Yarin Gal. NeurIPS Machine Learning for Health Workshop 2020.
A Bayesian Perspective on Training Speed and Model Selection. Clare Lyle, Lisa Schut, Robin Ru, Yarin Gal, Mark van der Wilk. Advances in Neural Information Processing Systems, 2020.[ArXiv pre-print]
Capsule Networks -- A Probabilistic Perspective. Lewis Smith, Lisa Schut, Yarin Gal and Mark van der Wilk. Spotlight paper at the ICML Workshop on Object-Oriented Learning: Perception, Representation, and Reasoning, 2020. [Workshop Paper] [ArXiv pre-print]
Influence of Outliers on Cluster Correspondence Analysis. Michel van de Velden, Alfonso Iodice D'Enza, Lisa Schut. Accepted for talk at CLADAG, Cassino Italy 2019. [Conference proceedings]
An Investigation into Different Architectures for Learning Word Representations. Lisa Schut, Adam Hare, Hans Hanley and Aditya Agarwal. Accepted as poster to OxCSC, Oxford United Kingdom 2019.
Counterfactual Explanations: Making AI Decisions More Useful and Trustworthy. Accenture Turing Innovation Symposium 2020
If you're interested in my CV or want to reach out, feel free to drop me a line at schut [at] robots [dot] ox [dot] ac [dot] uk. I'm always curious to hear about research internships (starting earliest summer 2021) or potential collaborations.