School of Computer Science and Statistics
The project is to survey censorship measurement tools and data sets (e.g. https://ooni.org/ and similar), to compare and contrast those, and then use some subset of the identified tooling and data to compare the censorship situation for Internet users based in Ireland against the position of users based in some other country, to be agreed … Read more
Individual fairness concerns the ability of a machine learning model to not being affected in its predictions by one or more sensitive features, such as gender, race, age etc.Recent methods developed techniques for the formal analysis and approximation of fairness in the case of deep Neural Networks (NNs). However such techniques are restricted to simple … Read more
Deep learning has recently achieved state-of-the-art performances in many computer vision classification tasks. In this project we’ll look into developing a tailored deep learning solution based on Neural Network for a problem related to classification with physiological signals. The project will go into details of architecture selection, hyper-parameter learning, validations, and best training practice of … Read more
Biometric authentication refers to systems that verify the identity of a user by unique traits such us fingerprints, voices or particular physiological features (such as ECG which will be the focus of the project). After having developed such a system based on publicly available data, this project will investigate the possibility of bypassing it using … Read more
Deep learning, in particular Neural Networks (NNs), has achieved state-of-the-art results in many applications in the last decade. However, the way these models work and operate is still not fully understood, and in many ways they are approached as black-box when deployed in practice.Unfortunately, this raises several concerns about their suitability to deal with sensitive … Read more
With the great capability of learning high-level representational features of unstructured data automatically, deep learning is acknowledged as a powerful machine learning algorithm for radio signal processing. For example, convolutional neural networks (CNNs) are leveraged to develop automatic modulation classification frameworks in [1]-[3]. CNN and its combination with Vision Transformers are also used to design … Read more
I am happy to supervise student-led projects in the areas of: online learning or the use of technology (e.g., Gen AI or lecture capture) in Higher Education; data analysis or applied statistics in the areas of higher education or student support services; and, statistics/mathematics education in Higher Education. Students interested in the this project should … Read more
Federated learning is a paradigm breakthrough shift in AI for data privacy preservation. Unlike conventional artificial intelligence (AI) techniques, federated learning does not require the users to share the data, but only the AI model parameters. As such, federated learning has found notable successes in numerous applications (e.g., Google keyboard, localization, security, and data sharing) … Read more
A general purpose processor (CPU) uses a pre-defined instruction-set architecture (ISA) to run common workloads with a reasonable performance. For certain workloads, this performance is CPU-bound, meaning that the pre-defined instructions are not able to use the silicon efficiently. In such cases, an accelerator including GPUs or FPGAs would be appropriate to improve the performance … Read more
In this project the student will explore three types of adaptive mechanisms that exist in modern general purpose processors (CPUs): branch prediction (prediction of condition results to help with fetching near-future instructions) and cache replacement (evicting the cache blocks that are less likely to be referenced soon). The main task in this project is to … Read more