Hi, my name is James and I build things. In 2012 graduated from UCL with a MSc in Computer Science, previous to that I studied at the University of Leeds. After graduating I was an inaugural cohort member of the Entrepreneur First graduate scheme. During which is tried out a few startup ideas (see below). I'm now currently working as a freelance software engineer.
You can find out more about me from my C.V and LinkedIn . To see some of my recent projects just visit my Github account. You can also follow me on Twitter, check out what I'm listening to on Last.FM, and look at my photos on Flickr.
You can email me at [first name]w[last name][at]gmail.com.
A company I co-founded at part of the Entrepreneur First graduate scheme. It is platform which aggregates different personal health and behavioral data streams from services such as Runkeeper and hardware such as Fitbit. The platform aims to help encourage positive behavioral change. A pre-alpha demo can be seen here.
Prototype Android app for managing diabetes. It allows diabetic patients to enter in their blood glucose levels alongside other information. This data can then be relayed back to their healthcare provider. The app also features a chat feature for the patient to speak with their nurse or doctor. The aim of the product was to increase patient adherence and allow doctors to intervene earlier when needed.
For my masters thesis I worked on a predictive model for the human body shape. Using a training set of body scans I created a predictive model in R. The model when given a limited number of input measurements for an individual can predict the rest of their body shape. The testing platform can be seen live here and the predictive model here.
Social Insight is a platform which allows brands and advertisers to monitor the brand's reputation across social media networks. At the core of the platform is a sentiment analysis algorithm to determine individuals sentiment towards the keywords specified. The platform also identifies the key influencer speaking about the brand and all data can be filtered by geographic and demographic information. The code used in the sentiment analysis algorithm can be seen on Github here.