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Dr Jose Hernandez-Lobato

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Research interests

My work in Bayesian machine learning includes the design and implementation of scalable methods for approximate inference and the construction, evaluation and refinement of probabilistic models that successfully describe the statistical patterns present in the data. During the last years I have designed new Bayesian machine learning methods with applications to the prediction of customer purchases in on-line stores, the modeling of price changes in financial markets, the analysis of the connectivity of genes in biological systems, the discovery of new materials with optimal properties or the design of more efficient hardware. I have focused on approaches based on probabilistic models, relying on methods for approximate inference that scale to large datasets. The results of this research have been published at top machine learning journals (Journal of Machine Learning Research) and conferences (NIPS and ICML).

Publications

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.

Join us.