Software and e-infrastructure
The scientific world runs on software - from tiny scripts to automate scientific tasks, to the millions of lines of code behind international efforts such as the Large Hadron Collider.
We are building the next generation of tools and infrastructure to support best practice for industrial and academic software engineering.
Our aim is to cultivate and improve research software practices, to support world-class research.
Our facilities
We boast an incredible array of facilities, making our innovative software and e-infrastructure research possible.
Areas of expertise
Our researchers focus their work in the following specialist areas:
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e-Science
Our eScience team is a multidisciplinary internationally leading research group focusing on the challenges of eScience. We specialise in data and knowledge-intensive e-laboratories.
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Information management
The design, development and use of data and knowledge management systems is vital so that the large amount of information we live with can be organised, retrieved, maintained and utilised confidently and securely across all settings, from research data to medical records.
Postgraduate research projects
Software and e-infrastructure projects
- Automatic Detection and Repair of Software Vulnerabilities in Unmanned Aerial Vehicles
- Combining Concolic Testing with Machine Learning to Find Software Vulnerabilities in the Internet of Things
- Component-based Software Development.
- Design and Exploration of a Memristor-enabled FPGA Architecture
- Exploiting Software Vulnerabilities at Large Scale
- Finding Vulnerabilities in IoT Software using Fuzzing, Symbolic Execution and Abstract Interpretation
- Job and Task Scheduling and Resource Allocation on Parallel/Distributed machines
- Managing the data deluge for Big Data, Internet-of-Things, Industry 4.0 environments
- Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing
- Security and privacy in p2p electricity trading
- Using Program Synthesis for Program Repair in IoT Security
- Verifying Cyber-attacks in CUDA Deep Neural Networks for Self-Driving Cars
Lucas Cordeiro projects
- Automatic Detection and Repair of Software Vulnerabilities in Unmanned Aerial Vehicles
- Combining Concolic Testing with Machine Learning to Find Software Vulnerabilities in the Internet of Things
- Exploiting Software Vulnerabilities at Large Scale
- Finding Vulnerabilities in IoT Software using Fuzzing, Symbolic Execution and Abstract Interpretation
- Using Program Synthesis for Program Repair in IoT Security
- Verification of Efficient Algorithms in Isabelle/HOL
- Verifying Cyber-attacks in CUDA Deep Neural Networks for Self-Driving Cars
Dirk Koch projects
Kung-kiu Lau projects
Mustafa Mustafa projects
Giles Reger projects
Rizos Sakellariou projects
- Job and Task Scheduling and Resource Allocation on Parallel/Distributed machines
- Managing the data deluge for Big Data, Internet-of-Things, Industry 4.0 environments
- Problems in large graphs (e.g., social networks, VANETs)
- Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing