I am a first-year PhD student in the Department of Computer Science, University of Cambridge, supervised by Prof Pietro Liò. My research is mainly focused on neural networks able to extract and exploit topological information from data. At the same time, I am working on the science of deep learning using tools from algebraic and differential topology.
In 2019 I have graduated with distinction the MPhil in Advanced Computer Science, while also receiving the Best MPhil Student Award. Over the summer of 2019 I interned at Google X, where I worked on Reinforcement Learning as part of the Everyday Robot Project. Previously, I did my undergraduate at The University of Manchester in the UK with an award-winning dissertation on Text to Image Synthesis using Generative Adversarial Networks supervised by Dr Jonathan Shapiro.
- We released a new preprint, On Second Order Behaviour in Augmented Neural ODEs, in which we study how Neural Ordinary Differential Equations learn 2nd order dynamics.
- Our paper Quantile QT-Opt for Risk-Aware Vision-Based Robotic Grasping was accepted to RSS 2020.
- We presented our new preprint Deep Graph Mapper: Seeing Graphs through the Neural Lens as a poster at the ELLIS Workshop on Geometric and Relational Deep Learning in Amsterdam.
- Happy to announce next summer I will be interning at Google Brain.
- Our paper Variational Autoencoders for Cancer Data Integration: Design Principles and Computational Practice has been published in the journal Frontiers in Genetics.
- Our paper Proximal Distilled Evolutionary Reinforcement Learning has been accepted at AAAI-20 in New York.
- Supervising the Cambrdige 3rd year course on Quantum Computing