School of Computer Science and Statistics
The sudden rise of adversarial examples (i.e., input points intentionally crafted so to trick a model into misprediction) has shown that even state-of-the-art deep learning models can be extremely vulnerable to intelligent attacks. Unfortunately, the fragility of such models makes their deployment in safety-critical real-world applications (e.g., self-driving cars or eHealth) difficult to justify, hence … Read more
Increasingly, patients gather data relevant to their care on their phones and via wearable or home-based sensors. But getting that data into a form that can be shared seamlessly with the healthcare system is a challenge. And clinicians have concerns about the quality of the data where it came from and to what extent they … Read more
If you have an interest in a machine learning task in the health space, and have access to suitable data, I am happy to supervise. (I am not an ML expert, but so long as you are using established techniques, we should be fine.)
I have supervised many projects involving the design and prototype development of apps and am happy to do more. Past examples include a mobile app to support development of patient self-efficacy, a mobile app to support suicide watch teams on the Corrib in Galway, a web application for supporting virtual work team productivity, and a … Read more
Increasingly Knowledge Graphs are underpinning Digital Humanities projects to support the representation and interlinking of data. For example in the recently launched Virtual Record Treasury of Ireland (VRTI), a KG is used to represent people, places, roles that appear in historical documents and their interconnection over the centuries. Typically these KGs are implemented using W3C … Read more
In this project we’ll look at the data shared by a set of similar apps on Android phones with a view to assessing their privacy. Typically there have been no measurements studies of the actual data shared by apps “in the wild”. Since network traffic is encrypted the project will involve some “white hat” hacking … Read more
In the world of big data and artificial intelligence, federated learning is a very attractive way of enabling data sharing in a privacy preserving manner. Clients in a federated learning network never access data from other clients directly and they model parameters they receive are formed from data aggregates. However, under certain conditions the models … Read more
Smartwatches are increasingly used to track a variety of health-related data, but the focus is mainly on automated tracking. This project will investigate different modalities for entering self-tracking information via smartwatch. The project will suit better students taking the CSU44051 Module (Human Factors), or who have previously taken a module in Human-Computer Interaction.
My main interests are in the graphics end of visualization i.e. use of graphics or perception-driven approaches to provide generalized improvements to the process of visualizing data or information. However I’m also willing to consider challenges of visualizing specific datasets or dataset types. Below are some key areas of interest (I’d be happy to supervise … Read more
The Zebra Puzzle is a well-known constraint satisfaction problem that ChatGPT knows about. But can ChatGPT solve the puzzle or problems like it step by step in accordance with the rules of logic? The aim of this project is to investigate how far ChatGPT is able to reason about such problems, and how ideas such … Read more