All Projects

Reassembly of archeological artifact fragments requires considerable time and manual effort for researchers along with a necessity to handle potentially fragile material. It would therefore be advantageous for this process to be automatic. In this project we will work on creating a method for matching 3D scans of ancient animal bone fragments in order to … Read more

As the need for privacy-aware sensing grows, Wi-Fi-based human pose estimation is emerging as a viable alternative to vision-based systems. However, transmitting and processing large volumes of channel state information (CSI) poses a significant challenge, particularly for edge devices with limited resources. This project proposes a scalable AI-driven framework that compresses CSI data using vector … Read more

As a piece of language, a narrative may be regarded as a sequence S of sentences about a sequence E of events. The possibility that the order of E does not align with S (violating so-called iconicity of sequence) is one of many challenges in understanding narratives. Others include the variety of granularities and the … Read more

The aim of this project is to understand the interplay between randomness and optimization in the choice of a Markov decision process and of a policy, working with simple examples such as tic tac toe and variants. Particular attention will be paid to entropy and its maximization.

Sports analytics increasingly relies on machine learning models to understand and predict player behavior, strategy, and outcomes. In team sports like rugby, pose estimation models can extract player keypoints (e.g., body joint locations) from match footage or sensor data, enabling automated performance analysis. However, despite recent progress in pose-based classification tasks (e.g., identifying tackles, passes, … Read more

Sign Language Recognition (SLR) is a field of Computational Linguistics that sits at the intersection of Computer Vision and Natural Language Processing – aiming to effectively extract salient linguistic features from visual data of sign language users. Recent SLR research has centered Machine Learning approaches, however, these methods typically rely on large-scale datasets which are … Read more

The Irish language is considered a low resource language as it has less data available for research, due to it being a minority language. This has implications on technological advancements in areas such as speech recognition, where limited data impacts the development of accurate and accessible digital tools. While transfer learning using multi-lingual models has … Read more

In many sports, coaches and athletes rely on annotated video footage to improve player performance, reduce the risk of injury, and analyse the game. This is also the case for rugby. Stakeholders at all levels, from amateur to professional, invest a lot of time and resources into annotating these games. With video quality and camera … Read more