Mr Alexandre Navarro

Contact information

Research interests

In many datasets, the driving cause for the behaviour we observe is tied to a hidden cause that would be measured using a scale that "wraps on itself" such as angles or a clock/calendar. More precisely, the topology of the latent space can be described as lying over a manifold comprised of combinations of circles, spheres or tori, which requires the tools of circular statistics. My research aims to study how to learn models using these variables in an efficient way through the framework of variational inference. I am also interested in the field of reinforcement learning and applications of machine learning for decision making.


About us

The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science.

The Centre is funded by a series of collaborations with partners in business and industry which have an interest in using data science for the benefit of their customers and their organisations. Our founding partner is Aviva, the UK’s leading insurance company. We work with industrial partners to build a portfolio of collaborative research projects, provide professional development opportunities for their own staff and access to the full breadth and depth of the University’s talent pool in the area of data science.

With unprecedented access to increasing volumes of data, our research ranges from the underlying fundamentals in mathematics and computer science, to data science applications across all six University Schools of Arts and Humanities, Biological Sciences, Clinical Medicine, Humanities and Social Sciences, Physical Sciences, and Technology.

In parallel, our research addresses important issues around law, ethics and economics, in order to apply data science to solve challenging problems for society.

C2D3 supports collaboration and knowledge transfer in this growing field.

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