Supervision of 3rd and 4th year project & Masters Practicum
I am open for supervision of 3rd and 4th year projects and Masters Practicum in the areas of:
- Applied Statistics and Big Data
- Computational biology
- Smart Cities
- Pedestrian/traffic behaviour
- Projects utilising data from OpenStreetMap or Google Maps in various contexts
- Joint projects with Suzanne Little around Park@DCU - an app to assist in finding appropriate parking across the DCU campuses based on both historical occupancy data, real-time updates and information such as location, nearby facilities, opening times, parking cost etc.:
- Joint projects with Lisa Loughney around MedEx Wellness - MedEx is a unique and new model of community-based chronic illness rehabilitation. Developed by Dublin City University (DCU) in 2006; it is a partnership between a third level educational institution and the healthcare setting. MedEx’s core concept is the provision of quality evidence-based exercise rehabilitation, supported by medical supervision, for people with diverse chronic illnesses. MedEx caters for 550 patient visits per week across 5 separate chronic illness programmes. These programmes are HeartSmart (cardiac rehabiliatation), BreatheSmart (pulmonary rehabilitation), Smart Steps (claudication rehabilitation), Diabetes Health Steps (diabetes care) and Move On (cancer rehabilitation).
We are currently conducting a 2-year single arm prospective trial to evaluate the effect of MedEx as a public health model for community-based chronic illness rehabilitation.
The MCM/research questions that we are addressing include:
- The effect of the MedEx Wellness Programme on physical outcomes
- The effect of the MedEx Wellness Programme on clinical outcomes
- The effect of the MedEx Wellness Programme on psychosocial outcomes
- Additional possible directions of thought:
CA4 project to create Park@DCU app using a Python backend framework with an SQL database, calling web services and having both a web and mobile app interface.
MCM project to create Park@DCU app by gathering and analysing data. Use historical data from estate office (or capture carpark over several days) Use visualisation tools. Use distributions to create realistic historical occupancy. Use ‘real-time’ occupancy data.
- Analysis of publicly available large data sets (for example census data for Ireland or UK) to pose questions (of your choice) and find relationships in population and economy data
- Simulation of movement behaviour of large groups of people using artificial intelligence/life algorithms such as Boids to avoid obstacles in indoor environments (such as buildings)
- Mobile applications that use OpenStreetMap or Google Maps data for real-time tracking of urban information of interest