School of Computer Science and Statistics
Forecasting conflict on a fine-grained grid level has real-life policy implications that can empirically inform meaningful healthcare and peace-preservation decisions. In many settings, interpretable models have the appeal that policymakers know how to draw conclusions from the model and do not have to base their decisions on black-box models. On the other hand, machine learning … Read more
This project will investigate how individuals adapt to each other during a dialogue. Rather than focusing on speech recordings only, this project will involve the data collection and analysis of neural data from electroencephalography from two individuals simultaneously as a dialogue unfolds. This is part of a bigger project led by a PhD students in … Read more
Restoring speech communication in individuals that can’t speak or have difficulty speaking (e.g., individuals with ALS) is an important challenge that could benefit many. While many solutions have been proposed that have various limitations, recent progress in machine learning methods (e.g., transformers) open new opportunities. This project aims to decode the intended speech of individuals … Read more
So-called ‘capacity drop’ is a phenomenon that sometimes occurs when joining vehicles interrupt the flow of traffic on a motorway, effectively reducing the capacity of the road. To address this problem, this project will investigate the design of a cooperative motorway on-ramp merging algorithm for automated vehicles. From the perspective of vehicles joining the motorway, … Read more
This project will investigate the use of reinforcement learning to develop a highway journey booking system incorporating a dynamic pricing strategy to allow traffic demand to be shaped in ways that will improve traffic efficiency and enhance sustainability by reducing emissions and fuel consumption. The goal will be to evaluate the potential benefit of the … Read more
A ‘digital twin’ is a digital model of a real physical artefact or environment that mirrors the state of its real-world counterpart (ideally) in real time by integrating data available via the ‘Internet of Things’ (IoT). A digital twin of a roadway would represent the physical road and its current traffic flow and provide a … Read more
Learning a second language is a challenging and time-consuming task. While a myriad of strategies have been proposed, we are still far from reaching an optimal personalised solution. Users either drop out early in the process or, once they reach a sufficient level of proficiency, they hit a plateau that seems impossible to overcome. This … Read more
The massive step up in how Large Language Model can generate convincing and often accurate content based on simple prompts has come as an unanticipated challenge to itching and learning in universities. While the reaction to date has focussed on how to address the risks of LLM being used for plagiarism, less focus has been … Read more
We will explore generative AI with a focus on 3D content creation and editing. You will build up your background in 3D computer graphics and 3D computer vision and conduct research in the following themes including neural radiance fields, diffusion models, or applied projects. 1. Neural radiance fields Project 1.1: Real-time neural radiance fields. We … Read more
Many projects are available in computational linguistics, artificial intelligence, cognitive science, etc. (see here — https://www.scss.tcd.ie/Carl.Vogel/main.2024-2025.shtml).