As the Internet-of-Things (IoT) emerges, the role of Information and Communication Technologies (ICT) has grown, facilitating direct interactions with the physical environment. This change underscores the need for robust, secure, and resilient ICT systems. Our work is dedicated to crafting innovative approaches and tools, aimed at helping stakeholders in the design, governance, evaluation, and upkeep of secure, top-tier IoT-based systems. This effort includes delving into sophisticated AI strategies for software engineering and customizing these practices to bolster AI applications, with the goal of achieving efficiency, reliability, and the highest standards of safety, security, and privacy in these technologies.
Research Interests
- Software Engineering: Focusing on the development of robust methodologies and practices to enhance the creation and maintenance of high-quality software systems.
- Cybersecurity: Specializing in the implementation of advanced security protocols and strategies to protect software systems from cyber threats.
- Software for Self-Adaptive Systems: Exploring the design and implementation of software capable of autonomously adapting to changing environments and requirements.
- Secure IoT Data Exchange: Assuring security and fostering confidence for IoT data sharing (aligned with standards) will enable secure data exchange between various parties along the IoT devices-Edge-Cloud computing continuum, the larger societal benefits of the IoT can be achieved.
- Data Quality: Develop software engineering and AI tools for data quality monitoring, metrics, and repair.
- Data Sovereignty: Researching acceptable use policies for data assets, privacy management, data economics, and establishing data sovereignty through federated data spaces. Data sovereignty enables an individual or an organization to control how, when, and at what price its data is used across the value chain.
- Smart IoT Software: Developing intelligent software solutions for IoT devices, emphasizing seamless integration and operational efficiency.
- Edge Computing: Researching the optimization of software for edge computing environments to enhance data processing and reduce latency.
- Privacy: Implementing trustworthiness methods to ensure the privacy and confidentiality of data within software systems.
- Security Risk Management: Applying comprehensive risk management frameworks to identify, assess, and mitigate security risks in software development and deployment.
- AI Engineering: Advancing the field of AI through the development of reliable and efficient AI systems, with a focus on integrating AI methodologies into software engineering practices and enhancing the trustworthiness of AI applications in terms of safety, privacy and security.
