James Lee

Dr. Neal Lathia

PhD Research

Evaluating Collaborative Filtering Over Time

N. Lathia
Department of Computer Science, University College London. June 2010.
Supervisors: Prof. Stephen Hailes, Prof. Licia Capra


Smartphone Application Research

As part of my research while at the University of Cambridge (2011-2015) and University College London (2010-2011), I have built and deployed a number of smartphone systems. These systems combine engaging interfaces, energy-efficient sensor data collection, and machine learning analytics to try and create interesting end-user experiences and data for multi-disciplinary research teams to analyse.

Q Sense

Q Sense was a context-aware, sensor-driven smoking cessation intervention. The app used geofencing, smoking self-reports, and a tag-based matching algorithm to deliver tailored smoking cessation support messages, and resurfaced the idea of using ratings in a health intervention. The research project that evaluated this app ran between 2013-2016.

Project Page

Emotion Sense

Emotion Sense was a mood-tracking "journey of discovery" app. It collected manual mood reports via experience sampling and behavioural data from sensors to support research into wellbeing in daily life. This app should not be confused with the previous research on classifying emotions from voice, which this app does not do due to privacy concerns. The press release following the app's public launch was covered extensively (The Times, Huffington Post, BBC) and the app was subsequently downloaded over 40,000 times. The research project ran between 2011-2016.

Project Page

The (Poo) Review

A quantified-self tool for tracking inflammatory bowel disease. This app was deployed in 2011 to test the feasibility of using ratings and implicit gamification in a health context.

Paper at the ACM Workshop on Mobile Systems for Computational Social Science, 2012.
Demo at ACM Recommender Systems, 2012.

Tube Star

An app for crowd-sourcing status updates and disruptions in the London Underground. The app was designed following an extensive analysis of London's Oyster card data. Tube Star was deployed in 2012; the paper linked below provides a thematic analysis of the content it generated.

Paper at the 11th Conference on Mobile and Ubiquitous Systems, 2014.

Academic Research Projects

Smartphone Sensing for Health Applications

EPSRC Impact Acceleration Account.
November 2014 - September 2015.

Q Sense: Smoking Cessation Smartphone Sensing App

MRC Public Health Intervention Development Scheme.
April 2014 - August 2015.

Project Page
MRC Network Magazine feature on mobile medicine.
Science Magazine feature on mHealth.

Ubhave: Ubiquitous and Social Computing for Positive Behaviour Change

January 2012 - March 2015.

Project Page
Emotion Sense Research

i-TOUR: intelligent Transport system for Optimized URban trips

European Commission Research: The Seventh Framework Programme.
July 2010 - December 2011.


Utiforo: Pervasive Computing Support for Market Trading

September 2006 - June 2010.

Project Page

Programme Committees

I review research broadly related to recommender systems, web technologies, information retrieval, ubiquitous computing, and data mining/artificial intelligence.