I'm a computer scientist and physicist passionate about interdisciplinary collaboration, learning and teaching, all things image processing, and Nutella. I'm particularly interested in the medical, agrotech, and educational spaces, and any work that can improve our well-being as humans.
I'm currently a Principal Data Scientist at CBRE, where I lead a team of data scientists working in forecasting revenue scenarios under COVID-19, analysing digital user behaviours using unsupervised learning, and bringing modern computational methods to engineers and stakeholders alike.
I attended the University of Warwick, in the UK, as a Bachelors of Chemistry student with a minor in Management.
I then joined the Centre for Complexity Science, where I earned a Masters in Complexity Science and a PhD in Computer Science in the field of mathematical neuroscience, under Dr. Yulia Timofeeva. I developed algorithms to compute the filtration properties of dendritic trees as a function of their morphologies.
I then worked as a postdoctoral researcher at Princeton University's Department of Ecology and Evolutionary Biology in Bryan Grenfell's group, studying the predictability of epidemics in small populations. During my postdoc, I also created and delivered courses in scientific computing for the Princeton Institute for Computational Science and Engineering.
I've also collaborated widely, on things like building image processing algorithms for automated histology, analysing antibiotic consumption, studying malaria transmission dynamics, and building remote-sensing hardware for mouse field studies.
I was born in France, and have also lived in the USA, the UK, Poland, Russia, and Canada. I've really enjoyed seeing some beautiful places and sampling different cultures (and food !).
I love reading, mostly fantasy and science fiction, but also philosophy and technical literature. I'm an avid cook and bread baker, and a scotch aficionado. I'm also a photographer and amateur radio operator.