Areas of Interest

Dr Phil Bartie - My research focus on spatial data science and the development of contextual awareness for mobile devices (e.g. robots, autonomous vehicles, wearables). This includes big data, real time visibility modelling from LiDAR sourced Digital Surface Models, using computer vision for object detection and face recognition, HCI, and spatial analysis.

Dr William Mackaness - Broadly my research is concerned with the application of statistical and visualisation techniques to geographical problem solving (including the use of exploratory data analysis). Beyond application, my interests are focused on theories of scale, and the characterisation of geographic space. There are significant challenges in modeling geographic space at multiple scales, in storing that information in a meaningful way such that it can support intuitive exploration of geographic pattern and process at multiple levels of detail. These ideas have relevance in real and virtual worlds, and present additional challenges when applied to the domain of location based services, and wayfinding services - two areas I am particularly interested in researching.

PhD Candidates
Megan Grace - I am PhD student studying at the University of Stirling. Over the course of my PhD, I will be investigating the potential of inland blue water spaces to equitably improve health and wellbeing across a population. My research project will involve utilising geospatial data to assess the ways in which the relationship between health and blue space can vary across the rural-urban continuum. 

Craig McDougall - I'm primarily interested in how the environments that we live in can positively or negatively influence our health and well-being, with a particular focus on access to the natural environment. My research combines geospatial approaches and large-scale survey-based health data to quantify the effects of neighbourhood access to blue and green space on mental health. I also use a range of stated preference techniques to establish the non-market economic value of access to bodies of freshwater in Scotland.

Computer Science Students
David Rimar - Carried out an MSc in Data Science at Heriot-Watt University. My research revolves around utilizing geospatial data from social media to track events relating to natural disasters in real-time. By applying machine learning models to classify tweets and showcasing affected areas by region on a web map. My work shows the usefulness of social media in detecting floods in the UK. My generic motivation is to use data science to generate insight and aid adequate responses relating to climate change.  

Ruvini Nanayakkarage - Completed an MSc in Data Science at Heriot Watt University. My research interests include machine learning, data analysis and data visualization with application to analysing and investigating data from public health sector. My research project was on detecting infectious diseases outbreaks occurred in UK in recent years using geospatial data from twitter.

Kusalka Silva - Finished an MSc degree in Data Science at Heriot-Watt University. My research project focused on developing an application that uses geospatial data for monitoring all posts on Twitter related to criminal activities and identifying regions that show a high number of crimes.

Anupam Shankar - I am pursuing masters degree in Data Science from Heriot-Watt university. My research project is focused on the spatial and temporal detection of events from tweets.

Akshay Venkataramana - Current student at Heriot-Watt University specialising in Computer Science (Software Engineering). My research involves spatial disease analysis utilizing data acquired through social media platforms such as Twitter.

Emma Aikamhenze - I am a final year Bsc Computer Science student at Heriot Watt university. My research project involves using Twitter data to detect trends in popular music, compiling statistical summaries and charts, and validating my findings against music streaming platforms (e.g deezer)