I am a final-year PhD student in the Department of Computer Science at the University of Oxford, supervised by Professor Thomas Lukasiewicz. In my research, I develop neuro-symbolic methods that integrate background knowledge constraints into neural networks, enforcing them during both training and inference.
I am particularly interested in incorporating such constraints into deep generative models for synthesising realistic tabular data. During my PhD, I demonstrated that complex constraints—from linear inequalities to disjunctions over linear inequalities that model non-convex and even disconnected spaces—can be successfully integrated during training to enhance the quality of synthetic data. My broader research vision is to bridge the gap between neuro-symbolic AI and real-world applications to build more robust and trustworthy systems.
Previously, I worked on detecting reflective symmetries in 3D models at Five AI. I completed my Bachelor’s and Master’s at The University of Edinburgh, where my Master’s thesis, supervised by Professor Sharon Goldwater, focused on speech-to-text machine translation.
News:
- May 2025: I received the Oxford PhD Runner-up Prize awarded by G-Research!
- April 2025: Presented at ICLR my recent work on deep generative modelling with constraints captured as quantifier-free linear real arithmetic formulae.
- February 2025: I attended the Dagstuhl Seminar on Logic and Neural Networks and presented the work I conducted during my PhD.
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