Faculty of Computer Science and Technology
About this community
Current research areas include bioinformatics, computer architecture, computer vision, distributed systems, graphics and human-computer interaction, logic and semantics, machine learning, natural language processing, networking and wireless communication, operating systems and virtualization, programming, security, and sustainable computing
The Computer Laboratory undertakes research in a broad range of subjects within the disciplines of Computer Science, Engineering, Technology, and Mathematics. Current research areas include bioinformatics, computer architecture, computer vision, distributed systems, graphics and human-computer interaction, logic and semantics, machine learning, natural language processing, networking and wireless communication, operating systems and virtualization, programming, security, and sustainable computing.
Collections in this community
Recent Submissions
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Mechanising and evolving the formal semantics of WebAssembly: the Web's new low-level language
(2021-11-27)WebAssembly is the first new programming language to be supported natively by all major Web browsers since JavaScript. It is designed to be a natural low-level compilation target for languages such as C, C++, and Rust, ... -
Data Summarizations for Scalable, Robust and Privacy-Aware Learning in High Dimensions
The advent of large-scale datasets has offered unprecedented amounts of information for building statistically powerful machines, but, at the same time, also introduced a remarkable computational challenge: how can we ... -
Neural Diagrammatic Reasoning
Diagrams have been shown to be effective tools for humans to represent and reason about complex concepts. They have been widely used to represent concepts in science teaching, to communicate workflow in industries and to ... -
The Impact of Randomisation in Load Balancing and Random Walks
The real world is full of uncertainties. Classical analyses usually favour deterministic cases, which in practice can be too restricted. Hence it motivates us to add in randomness to make models similar to practical ...
