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Amazon Machine Learning Director is joining IDIAP’s International Advisory Board

Neil Lawrence, Director of the Amazon Machine Learning hub in Cambridge is a new member of the IDIAP Research Institute's International Advisory Board.

IDIAP
The Valais-based research institute IDIAP welcomes Prof. Neil Lawrence, director of the Amazon Machine Learning hub, to its International Advisory Board | © IDIAP

The IDIAP research institute is proud to welcome the new member of its International Advisory Board, Neil Lawrence. Professor of Machine Learning at the University of Sheffield, he is currently on leave of absence based at Amazon in Cambridge where he is Director of Machine Learning.

Neil’s main research interest is machine learning through probabilistic models. He focuses on both the algorithmic side of these models and their application. His recent focus has been on the deployment of machine learning technology in practice, particularly under the banner of data science. He is also the co-host of the Talking Machines podcast.

The IDIAP Advisory Board is comprised of members of the scientific community selected by the institute’s management for their exceptional skills and avant-garde vision. Although their role is strictly advisory, their advice is frequently sought when making decisions regarding research, training, and technology transfer.

Artificial Intelligence for Society

Located in Martigny in the canton of Valais, the IDIAP Research Institute is an independent, nonprofit research foundation affiliated with the Ecole Polytechnique Fédérale de Lausanne (EPFL). Its activities encompass basic research, training (graduate and post-graduate level), and technology transfer activities in the area of Artificial Intelligence for Society including, among others, multimedia information management, human-computer interaction, perceptual and cognitive systems, natural language processing and understanding, social media, biometric person recognition, multimodal information interfaces, applied artificial intelligence (AI) and large-scale machine learning.

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