Davide Zilli

I am a Research Scientist at Mind Foundry, an Oxford University's spin-off founded by Professors and Machine Learning luminaries Steve Roberts and Mike Osborne. We apply the latest advances in Machine Learning theory and practise to large-scale, complex commercial settings to provide advanced analytics. We work with all sorts of data, from sensor readings to financial time series. [If this sounds interesting and you would like to join our team, please drop me a line]

In the recent past I've been a Junior Research Fellow at Somerville College, University of Oxford, where I tutored undergraduate and visiting students on computer networks and software design. I was also a Post-doctoral Research Assistant in the Engineering Department of the University. My research interests lie in the application of machine learning algorithms to the monitoring of the natural environment. More broadly I'm interested in computer science, data science and bioacoustics. As a PDRA, I've lead the engineering efforts of the HumBug project, a Google-funded partnership with the Royal Botanic Gardens, Kew, that aims to automate the detection and classification of mosquitoes that carry malaria and similar diseases.

I obtained a PhD from the Institute for Complex Systems Simulations, in Electronics and Computer Science at the University of Southampton. As part of my doctoral research, I visited Microsoft Research Cambridge as a research intern, working on open hardware for bioacoustic classification, and MIT senseable city lab, where I was researching pervasive systems in the urban space.

My PhD, under the supervision of Alex Rogers and Geoff Merrett, involved using smartphones to monitor biodiversity. We developed a citizen science platform and a mobile system aimed at rediscovering a very endangered insect, called the New Forest cicada. This insect emits a very high-pitched call, difficult for most adults to hear, but easily detected by a smartphone. If you would like to know more about this project, please visit the project webpage.