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[2017-10-27] Prof. Roderick Murray-Smith, Glasgow University, "Sensing, Machine learning and Inference for controlling the human-computer interaction loop”

專題討論演講公告
張貼人:Seminar專用帳號2公告日期:2017-10-12

Title: Sensing, Machine learning and Inference for controlling the human-computer interaction loop
Date: 2017-10-27 2:20pm-3:30pm
Location: R103, CSIE
Speaker: Prof. Roderick Murray-Smith, Glasgow University 
Hosted by: Prof. SD. Lin


Abstract

This talk will focus on the use of inference and dynamical modelling in human-computer interaction. The combination of modern statistical inference and real-time closed loop modelling offers rich possibilities in building interactive systems, but there is a significant gap between the techniques commonly used in HCI and the mathematical tools available in other fields of computing science. Dealing with these complex sources of human intention requires appropriate mathematical methods; modelling and analysis of interactions requires sophisticated methods which can transform streams of data from complex sensors into estimates of human intention. I will illustrate how to bring these mathematical tools to bear on interaction problems, and will cover basic theory and example applications, including interaction with large music collections. This will include our work on the Bang & Olufsen Beomoment product and Syntonetic’s Moodgalaxy which combines Gaussian process priors, nonlinear dimensionality reduction and inferred moods to give you new ways to explore your music collection. I will also summarise some of our recent work on using the entropy of inferred mood and genre features to understand users’ criteria for playlist curation). 

I will describe some work done together with the Optics group in Physics ( QuantIC Quantum Imaging Hubhttps://quantic.ac.uk/innovation/technology/work-package-1-image-with-correlation  ), comparing Deep Convolutional Autoencoders with classical inverse problem approaches and linear transformations of Gaussian process priors for solving inverse problems in Single Pixel Cameras. Single pixel cameras combine a Digital Mirror Array with a single exotic sensor. This allows rapid prototyping of sensors with specific properties and frequency ranges, which allows them to go beyond conventional silicon sensors.


Biography

Roderick Murray-Smith is a Professor of Computing Science at Glasgow University, leading the Inference, Dynamics and Interaction research group, and heads the 50-strong Section onInformation, Data and Analysis, which also includes the Information RetrievalComputer Vision & Autonomous systems and IDEAS Big Data groups. He works in the overlap between machine learning, interaction design and control theory. In recent years his research has included multimodal sensor-based interaction with mobile devices, mobile spatial interaction, AR/VR, Brain-Computer interaction and nonparametric machine learning. Prior to this he held positions at the Hamilton Institute, NUIM, Technical University of Denmark, M.I.T., and Daimler-Benz Research, Berlin, and was the Director of SICSA, the Scottish Informatics and Computing Science Alliance (all academic CS departments in Scotland). He works closely with the mobile phone industry, having worked together with Nokia, Samsung, FT/Orange, Microsoft and Bang & Olufsen. He was a member of Nokia's Scientific Advisory Board and is a member of the Scientific Advisory Board for the Finnish Centre of Excellence in Computational Inference Research.



最後修改時間:2017-10-12 PM 3:31

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