My Philosophy

Fog & Edge

Fog/Edge Computing is an emerging paradigm that extends the capabilities of cloud computing to the edge of the network, enabling data processing and storage to be closer to the end users and devices, and providing low-latency, high-bandwidth, and context-aware computing services. 

My research on Fog/Edge Computing intersects with several key areas, including application placement, resource allocation and provisioning, energy awareness, and reliability. Through my work, I aim to develop novel algorithms and techniques that can optimise the placement of applications in Fog/Edge Computing systems, adaptively allocate and provision resources based on changing workloads and availability, balance energy consumption and performance, and enhance the reliability and fault tolerance of these systems. By focusing on these critical aspects of Fog/Edge Computing, my research has the potential to significantly improve the performance, efficiency, and scalability of edge computing applications, while enabling new use cases and applications that can benefit businesses and society as a whole.

Cybersecurity

Cybersecurity is the practice of protecting computer systems, networks, devices, and data from unauthorised access, theft, damage, or other malicious attacks. Cybersecurity involves a range of technologies, processes, and practices designed to prevent, detect, and respond to cyber threats and vulnerabilities, and to maintain the confidentiality, integrity, and availability of digital assets.

My research on cybersecurity focuses on several critical areas, including IoT security, blockchain technology, and Fog/Edge Computing. Specifically, I am investigating novel approaches to securing IoT devices and networks, including the development of secure communication protocols, access control mechanisms, and intrusion detection systems. Additionally, I am exploring the potential of blockchain technology to enhance the security and privacy of IoT systems, by enabling distributed trust, authentication, and tamper-proof data storage. Finally, I am investigating the unique security challenges and opportunities presented by Fog/Edge Computing, such as resource constraints, mobility, and distributed processing, and developing new techniques and algorithms to address these challenges. Through my work, I aim to advance the state of the art in IoT security and privacy, and to help ensure the safe and secure adoption of emerging technologies like blockchain and Fog/Edge Computing in a wide range of industries and applications."

AI and ML

Artificial Intelligence (AI) and Machine Learning (ML) are playing an increasingly important role in Fog/Edge Computing and Cybersecurity. In the context of Fog/Edge Computing, AI and ML techniques are being used to optimise resource allocation and management, enable autonomous decision-making, and provide predictive maintenance and fault detection for connected devices and systems. In the context of Cybersecurity, AI and ML are being used to detect and prevent cyber threats and vulnerabilities, and to enhance the security of digital assets. 

My research in the field of Artificial Intelligence and Machine Learning focuses on several key areas, including ML-based modeling, AI and ML techniques for Fog/Edge Computing, and deep learning. Specifically, I am exploring the use of ML techniques for developing accurate and efficient models for complex systems, such as those found in healthcare, finance, and energy. In addition, I am investigating the potential of AI and ML techniques for optimising resource allocation and scheduling in Fog/Edge Computing systems, which have unique constraints and requirements compared to traditional cloud systems. Finally, I am exploing deep learning techniques for detecting vulnerabilities, attack mitigation and other applications, with the aim of developing more accurate and robust models that can handle complex, real-world scanario. Through my research, I aim to advance the state-of-the-art in AI and ML, and to enable the development of more sophisticated and intelligent systems that can provide value across a wide range of industries and applications.