I am a Postdoctoral Research Associate in the Mathematics Department at Imperial College London, where I primarily work with Nick Jones. My academic work is concerned with the structure of large networks, such as social or communication networks, dynamics unfolding on networks, and inference techniques that allow us to learn as much as possible about social networks without compromising the privacy of individuals.
More recently, I have started developing generative models for wastewater-based epidemiology as part of the Envirology project where I am an RCoI. Before joining the project, I was a Staff Machine Learning Engineer at Spotify, where I focused on building large-scale content analysis pipelines to enrich the Spotify catalogue.
Hoffmann T, Jones NS, 2020, Inference of a universal social scale and segregation measures using social connectivity kernels, Journal of the Royal Society Interface, Vol:17, ISSN:1742-5662
et al., 2020, Community detection in networks without observing edges, Science Advances, Vol:6, ISSN:2375-2548
et al., 2019, Precision identification of high-risk phenotypes and progression pathways in severe malaria without requiring longitudinal data, Npj Digital Medicine, Vol:2, ISSN:2398-6352
Hoffmann T, Lambiotte R, Porter MA, 2013, Decentralized routing on spatial networks with stochastic edge weights, Physical Review E, Vol:88, ISSN:1539-3755