Dr. Aiden Doherty

Aiden Doherty is a postdoctoral researcher in CLARITY. His research interests cover lifelogging, environmental data management, sports & personal health IT applications, location aware computing, multimedia information management, and data mining. He has approximately 25 publications, has given 12 seminar/invited talks and had a three month internship with Microsoft Research in Redmond, WA, USA. He has also released the source code of a lifelogging browsing system, which has already had almost 200 downloads in its first 4 months, to enable the field proceed more efficiently. He holds a 1:1 BSc in computer science from the University of Ulster, and at the age of 24 a PhD from Dublin City University where he was a government of Ireland research scholar.

Aiden's primary research interest is in the area of passive personal life recording, predominantly in the sense of having a visual diary of oneself. A recent study has shown the potential of this area, where UK researchers, using fMRI scans, noted that SenseCam images appear to provide exceptionally strong memory cues. This may be helpful for those in the early stages of dementia. A big problem that cognitive and clinical neuropsychologists are having with this device is coping with the incredible volume of images generated. Aiden's visual information management research is focused on solving these challenges. Indeed Aiden is currently in close collaboration
with the University of Leeds on investigating the effectiveness and strength of retrieval cues offered by automatically "cherry-picked" SenseCam images. Other collaborations include investigating the SenseCam as a tool to understand population health (Dept. Of Public Health & Primary Care, University of Oxford); investigate behavioural/lifestyle characteristics (Clinical Research Centre St. Vincent's); explore how social functioning can be maintained (TRIL research centre & St. James's Memory clinic); etc.

Aiden is also heavily involved in the management, usage, and summarisation of environmental data from a wide variety of sources, e.g. domestic electricity consumption from 20+ homes, water quality data, landfill air quality data, etc. He also has research interests in multimedia indexing & searching, sports & personal health applications (particularly sensors to assist in quantifying fatigue factors in ultra-endurance cycling), inferring lifestyle patterns from energy usage in one's home, eye tracking devices to evaluate interfaces, and other forms of data mining.