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Nando De Freitas Computer scientist

Nando de Freitas wants to understand intelligence and how brains work. His key areas of research are neural networks and deep learning, reinforcement learning, apprenticeship learning and teaching, goal and program discovery, transfer and multi-task learning, reasoning and cognition.

Nando is a strong believer in building artificial intelligence (AI) tools to improve health care, advance science and provide decision support systems for lawyers, economists, politicians, environmentalists and all sorts of people who are interested in improving the lives of every creature in this planet of ours. The price to pay for not developing AI tools to extend our minds so as to solve these complex problems is simply too high.


Charles A. McDowell Award for Excellence in Research, 2013.

Distinguished Paper Award at IJCAI, 2013.

MITACS Young Researcher Award, 2010.

Relevant Publications

S. Reed and N. de Freitas, "Neural Programmer-Interpreters," ArXiv preprint (Nov. 19, 2015).

Z. Wang, N. de Freitas and M. Lanctot, "Dueling network architectures for deep reinforcement learning," ArXiv preprint (Jan. 8, 2016).

Z. Wang et al, "Bayesian optimization in high dimensions via random embeddings," International Joint Conferences on Artificial Intelligence (IJCAI) (2013).



Senior Fellow Learning in Machines & Brains


University of OxfordDepartment of Computer Science


PhD (Bayesian Methods for Neural Networks) Trinity College, Cambridge University

BSc (Engineering) University of Witwatersrand


United Kingdom

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