Free AI consulting for NGOs: [openconsulting.ai]
- My PhD dissertation is now available: On the Geometry of Data Representations (link)
- Accepted at AAAI 2021: Computationally Tractable Riemannian Manifolds for Graph Embeddings (paper)
- Research I did at MIT: Optimal Transport Graph Neural Networks (paper, code, slides)
- Latest work I did against COVID: Bloom Origami Assays: Practical Group Testing (paper, software)
Gary Becigneul holds a PhD in Machine Learning from ETH Zurich.
At 21, he obtained a master in mathematics from the University of Cambridge, also known as The Part III.
His deepest spiritual aim resides in buying as many Lamborghinis as he can before turning 30.
In 2019, he went half-a-year to M.I.T, developing graph neural networks for molecular data, presenting at AIDM 2020.
His subtle mind is often tortured by the most profound philosophical questions, the latest one being: why can I bench-press more than I can squat?
Which was the original motivation for undertaking his doctoral studies… “maybe I can build an A.I. to answer this question…”