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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Human computer systems
Understanding how humans use and interact with computing systems is critical, and part of our core mission. We blend expertise in interface design with psychology theories, to build more intuitive computing systems.
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Information management
We design, develop and build state of the art data and knowledge management systems -- spanning from formal underpinnings in knowledge representation and logic, to challenging interdisciplinary work.
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Postgraduate research projects
Software and e-infrastructure projects
- (MRC DTP) Data-Science Approaches to Better Understand Multimorbidity and Treatment Outcomes in Patients with Rheumatoid Arthritis
- (MRC DTP) Unlocking the research potential of unstructured patient data to improve health and treatment outcomes
- Advising on the Use and Misuse of Collaborative Coding Workflows
- 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.
- Computational Models to Predict Overnight Hypoglycemia in Type 1 Diabetes
- 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 systems including Cloud, Edge, Fog Computing
- Managing the data deluge for Big Data, Internet-of-Things and/or Industry 4.0 environments
- Predicting Blood Glucose from Nutrition Analytics for Type 1 Diabeties
- Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing
- Security and privacy in p2p electricity trading
- Security-Minded Verification for Autonomous Systems
- Type 1 Diabetes: Accurate Prediction of Glucose Absorption from Food
- Using Program Synthesis for Program Repair in IoT Security
- Verifying Cyber-attacks in CUDA Deep Neural Networks for Self-Driving Cars
Lucas Cordeiro projects
- Application Level Verification of Solidity Smart Contracts
- 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
- Verifying Cyber-attacks in CUDA Deep Neural Networks for Self-Driving Cars
Louise Dennis projects
Clare Dixon projects
Suzanne Embury projects
Simon Harper projects
Dirk Koch projects
Kung-kiu Lau projects
Mustafa Mustafa projects
Goran Nenadic projects
- (MRC DTP) Data-Science Approaches to Better Understand Multimorbidity and Treatment Outcomes in Patients with Rheumatoid Arthritis
- (MRC DTP) Unlocking the research potential of unstructured patient data to improve health and treatment outcomes
- Integrated text and table mining
- Text Analytics and Blog/Forum Analysis
Giles Reger projects
Rizos Sakellariou projects
- Job and Task Scheduling and Resource Allocation on Parallel/Distributed systems including Cloud, Edge, Fog Computing
- Managing the data deluge for Big Data, Internet-of-Things and/or Industry 4.0 environments
- Problems in large graphs representing social networks
- Scheduling, Resource Management and Decision Making for Cloud / Fog / Edge Computing