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- Kairui Zhang PhD Bristol 2024 - current, cosupervised with Dr Zahraa Abdallah
- Jasmine Owers (PhD Bristol 2023 - current, cosupervised with Dr Edwin Simpson. MSc Data Science, Bristol, 2021).
- Beth Pearson PhD Bristol 2023 - current, cosupervised with Dr Mike Wray
- Xiaoyu Tong (PhD UvA 2021 - current, co-supervised with Prof. Ekaterina Shutova)
- Bilal Boulbarss (MSc Data Science, Amsterdam, 2025)
- Lili Bognar (MSc Data Science, Amsterdam, 2025)
- Ananay Wahedra (MSc Data Science, Amsterdam, 2025)
- Rens Roelen (MSc Data Science, Amsterdam, 2025)
- Clio Feng (MSc AI, Amsterdam, 2025)
- Henrietta Chen (MSc Logic, Amsterdam, 2025)
- Philipp Hellwig (MSc Psychology, Amsterdam, 2025)
- Zhijin Guo (PhD Engineering Maths, Bristol, 2021-2024)
- Changshuo Wang (MSc Engineering Maths, Bristol, 2022) Changshuo's research is in extending neural methods for building density matrices.
- Qiming Chen (MSc Engineering Maths, Bristol, 2022) Qiming looks at modelling generic sentences with density matrices.
- Mike Nelhams (MEng Engineering Maths). Mike is looking at using density matrices on larger-scale entailment datasets.
- Ben Lippold (MEng Engineering Maths, Bristol, 2022). Ben is investigating the interaction of metaphor and natural language inference.
- Shuhao Zhang (MSc Data Science, Bristol, 2021). Shuhao looked at novel approaches to building word region embeddings.
- Jiaqi Wu (MSc Data Science, Bristol, 2021). Jiaqi investigated the performance of neural density matrices to encode hyponymy.
- Xiaoyu Tong (MSc Brain and Cognitive Sciences, UvA, 2020, co-supervised with Ekaterina Shutova). Xiaoyu built a large natural language metaphor paraphrase dataset and undertook a systematic review of neural methods for metaphor processing in NLP.
- Francois Meyer (MSc AI, UvA, 2020). Francois built a neural model for generating density matrix word embeddings, showing how these embeddings can represent multiple senses of words which are disambiguated in the process of composition.
- Verna Dankers (MSc AI, UvA, 2019, co-supervised with Ekaterina Shutova). Verna developed a multitask learning architecture to jointly detect metaphor and emotion, as well as a heap of other stuff!
- Yaared al-Mehairi (MFoCS, Oxford, 2016, co-supervised with Bob Coecke). Yaared worked on linking the DisCoCat model with Smolensky's Integrated Connectionist-Symbolic model.
- Dea Bankova (MFoCS, Oxford, 2015, co-supervised with Bob Coecke). Dea worked on the use of density matrix models for hyponymy and entailment.