About SEA

The main aim of the Software Engineering at Aston (SEA) research group is to enable organisations to create and maintain better software, better.

We develop concepts, theories and tools to construct systems that solve our problems reliably in the face of ever increasing complexity and uncertainty. Our main approach is to increase the level of abstraction at which software systems operate, bringing them closer to the problems to be solved. Our research has been applied to web engineering, service-oriented architectures, digital health systems and high-integrity systems engineering, among other areas.

SEA News

SEA seminar - History-Awareness in Self-Adaptive Systems by Lucas Sakizloglou

09/11/2020

Lucas Sakizloglou, researcher from the System Analysis and Modelling Group of the Hasso Plattner Institute, presented his work to SEA. Lucas's research is related to runtime models, temporal logic and graph queries to enable history-aware self-adaptation.

Systems Analysis and Modelling (SAM) paper presentations

19/10/2020

The SEA members Juan Parra and Owen Reynolds presented the papers: Temporal Models for History-Aware Explainability and Towards automated provenance collection for runtime models to record system history at the 12th System Analysis and Modelling Conference SAM 2020, co-located with MODELS 2020.

Models and Evolution (ME) paper publication

16/10/2020

The SEA member Owen Reynolds presented the paper: Automated provenance graphs for models@run.time at the 14th Workshop on Models and Evolution (ME) 2020, a satellite event at MODELS 2020.

Academic staff

Prof. Pete Sawyer

Pete's primary interests are software requirements, and how they impact the rest of the software life-cycle. Pete is also interested in digital health and natural language processing for software engineering.

Prof. Tony Clark

Tony is working on the XModeler meta-tool for language-based Software Engineering and the application of actor-based languages to complex system understanding through simulation and analysis.

Dr. Nelly Bencomo

Nelly exploits the interdisciplinary aspects of software engineering, comprising both technical and human concerns, while developing techniques for intelligent, autonomous and highly-distributed systems.

Dr. Antonio Garcia-Dominguez

Antonio's research interests are on software testing, model-driven engineering and novel methods for engineering education.

Dr. Paul Grace

Paul’s research interests are in the development of systems software to support security and privacy in distributed systems. He is interested in dynamic security to identify and control treats at runtime. He also develops user-centric privacy preserving middleware technologies.

Dr. Luis Manso

Luis' research interests include autonomous robotics, software engineering for robotics, active perception, task planning, and human-robot interaction.

Research Associates

Luis Hernan Garcia Paucar

Luis' research interests are on techniques to improve the decision-making process in self adaptive and autonomous software systems, under dynamic and uncertain contexts at runtime. Luis is also interested on RL and Deep Learning techniques for Software Engineering.

Imane Guellil

Imane is interested in Natural Language Processing, including areas such as sentiment analysis, automatic translation and more recently, named entity recognition and disambiguation. In her role as KTP Associate with FoldingSpace, Imane is applying her research to an industrial context.

PhD students

Juan Marcelo Parra Ullauri

Juan Marcelo's research interests include model-driven engineering, autonomous self-adaptive systems and explainability in autonomous systems. Juan is interested in applying these approaches to cyber-physical systems, internet of things and ambient assisted living contexts.

Owen Reynolds

Owen is researching self-explanation for self-adaptive systems, that use well-defined models using model-driven engineering methods.

Huma Samin

Huma's research interests are on self adaptive systems and autonomous systems and applying machine learning and deep learning techniques to achieve self-adaptive capabilities at runtime.

Jomar Alcantara

Jomar’s interests lies in machine learning and natural language processing techniques and their application to healthcare systems. He is currently researching the application of these techniques to the early diagnosis of Mild Cognitive Impairment and Early Dementia.