Replying to an emails on a mobile device can be a challenge, even for short replies. What if there were a system that could automatically determine if an email was answerable with a short reply, and compose a few suitable responses that you could edit or send with just a tap?
Smart Reply, which will be launching later this week, is built on a pair of recurrent neural networks, one used to encode the incoming email and capture the gist of what is being said and the other to predict and compose grammatically correct possible responses.
Head over to the Google Research blog to learn more.
...still a waste of money.
In another example of how Deep Neural Networks (DNNs) can be used to create interesting works of art, a group of German researchers have released the paper, A Neural Algorithm of Artistic Style (http://goo.gl/HsFR0C), that introduces a system that renders an input photo in the artistic style of a given piece of art while preserving its overall content.
In their paper, the authors describe how the representations of content and style in their Convolutional Neural Network (CNN) are separable, making it possible to use neural representations to separate and recombine content and style of arbitrary input images. To learn more, read the full paper. For access to their algorithm, visit http://goo.gl/jB7ovU
- Lancaster UniversityPhD, 2010 - present
- Lancaster UniversityMRes - Innovation in the Digital Economy, 2009 - 2010
- Lancaster UniversityBSc (Hons) - Computer Science with Software Engineering, 2006 - 2009
- Cricklade CollegeBND - IT Practioners (Software Development), 2004 - 2006
- Fallout Shelter
- Hitman GO
- The Room Two
My research interests lie in exploring software engineering for the betterment of society, in particular healthy ageing. My current focus (on the SAMS project) is on the early detection of mild cognitive impairment and neurodegenerative diseases, such as Alzheimer’s disease, to enable earlier treatment and better quality of life. This is achieved through passive, opportunistic monitoring of computer users. Software captures participants’ interactions with their computers, for example collecting: mouse movement and key presses, application interactions, text analysis etc. Detecting dementia earlier can lead to improving the long term outcome of (e.g.) Alzheimer disease, and earlier treatment of other disorders such as depression, anxiety and other underlying medical conditions. Going forward I will be exploring the broad area of healthy ageing, specifically from a computer science and software engineering perspective. I have a strong interest in applying various techniques to complex problems in the Healthy Ageing field, and thrive in collaborative scenarios.
My PhD research explored the education of software engineers using a studio-based approach. This thread of research was grounded in transferring knowledge of design education (architecture, product design, art etc.) into a software engineering context. This also relates to a broad interest of collaboration in software development teams.
I am a digital innovation researcher (Ph.D. student), and part of the first cohort of the HighWire DTC. My background is in Computer Science and Software Engineering, and I have been immersed in cross-discipline research during the PhD and research positions since. I have a wide and varied interest in computer science and software engineering including healthcare technologies, healthy ageing, HCI, collaborative technologies, interactive systems, and software engineering education.
- Lancaster University, School of Computing and CommunicationsResearch Associate, 2014 - present
- Lancaster University, School of Computing and CommunicationsTeaching Assistant (Practicals & Tutorials), 2010 - 2013
- Lancaster University, CesagenSoftware Developer (Intern), 2009 - 2009
- Greggs of CumbriaSales Assistant + Sunday Man, 2007 - 2008
- Sodexho DefenceMess Hand, 2006 - 2006