School of Computer Science and Statistics
The performance of artificial intelligence based learning models is often initially assessed using well established benchmark datasets. However, satisfactory performance on these datasets does not guarantee similar performance in real-world settings where the data may be significantly more imbalanced. For example, in a medical dataset a positive diagnosis may be a relatively rare event and … Read more
Intelligent Transport Systems (ITS) are transforming traffic management by enabling real-time connections between vehicles, people, and services. Vehicles equipped with advanced sensors and 6G connectivity interact with roadside units for immediate data exchange, enhancing safety and traffic flow in smart cities. Traditional short-range communication methods, like Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I), cannot meet the needs … Read more
Have experience with and your own FYP/MSc project idea related to Reinforcement Learning (“plain” or multi-objective, multi-agent, transfer, lifelong, explainable, inverse, etc?) – whether to develop new algorithms or to apply existing ones to a new application area? Contact me with your idea to see if we can formulate the topic together.
This project will explore use of and development of new multi-agent RL techniques to achieve cooperation and coordination between autonomous vehicles in order to optimize traffic congestion. Prior experience with RL is essential
This project will apply and extend multi-objective (MO) technique Deep W-Networks[1] to a number of benchmark environments from multi-objective gym [2], and benchmark against other MO RL techniques. References: [1] J Hribar, L Hackett, I Dusparic. Deep W-Networks: Solving Multi-Objective Optimisation Problems With Deep Reinforcement Learning. International Conference on Agents and Artificial Intelligence (ICAART) 2023 … Read more
This project will investigate existing software testing techniques and development of new ones for testing of reinforcement learning-based software applications. References: [1] Yuteng Lu, Weidi Sun, Meng Sun, Towards mutation testing of Reinforcement Learning systems, Journal of Systems Architecture, Volume 131, 2022, https://www.sciencedirect.com/science/article/pii/S1383762122001977 [2] Miller Trujillo, Mario Linares-Vásquez, Camilo Escobar-Velásquez, Ivana Dusparic, and Nicolás Cardozo. … Read more
In the recent years causal inference has emerged as an important approach for addressing different issues within RL. Providing agents the ability to leverage causal knowledge was identified as a key ingredient in developing human-centered explanation methods. Namely, when using AI systems, humans tend to be interested in answering questions such as “What caused the … Read more
This project is in collaboration with the joint School of Medicine/ADAPT health research project called PARADISE. ANCA Vasculitis is a rare auto-immune disease in which sufferers are susceptible to flares, whereby a person’s immune system attacks their own body. Treating people with vasculitis is difficult, because the most successful treatments, such as rituximab, have significant … Read more
Please use this form to arrange a time to meet me to discuss project supervision: https://forms.gle/G82EJhXymGU3Wbf58 I have the below projects available, all related to Natural Language Processing: Data Collection for Analysis of Language in Video; Video Sentiment Analysis; Automatic Video Transcription; Automatic Identification of bias in Video Language; Automatic Prediction of Video Content Quality; … Read more
Edge computing has emerged as a promising solution for delivering services that demand low latency, high bandwidth, and stringent privacy requirements in numerous data- and compute-intensive applications, such as those in Smart Cities. Heterogeneity in edge computing resources and diverse application requirements demand adaptive optimization techniques, such as service placement, to conform to changing conditions. … Read more