is an Assistant Professor (Research) in the Centre for Computational Sciences and Mathematical Modelling. Before that he was a Research Fellow in Cyber Systems Engineering in WMG at the University of Warwick. He received his BE degree in Electronics and Communication engineering from Tribhuvan University, Nepal, the MSc degree in Embedded Systems from the University of Kent, England, and the PhD degree in the Institute for Digital Communications, within the School of Engineering, University of Edinburgh, Scotland. His research interests include computer vision, mobile computing, cyber security, and reinforcement learning, adversarial machine learning and communication etc.

My research focuses on applying Reinforcement Learning (RL) to address real-world challenges in the IoT ecosystem, particularly within wireless communication. Given RL's adeptness at learning and adapting from environmental feedback, it is uniquely positioned to navigate the multifaceted challenges of the IoT landscape. Specifically, I aim to tackle issues such as adapting to congested wireless channels, extending the battery life of resource-constrained devices, and proactively countering real-time security threats.

By achieving efficient bandwidth utilization and reduced latency, we can ensure not only seamless device-to-device communication but also unlock the potential for groundbreaking IoT applications—from autonomous vehicles to remote surgeries. RL's dynamic learning capabilities empower devices to adjust and fortify their security measures against evolving threats, underlining the importance of resilience in our connected systems.

In alignment with the United Nations' Sustainable Development Goal 9, my research seeks to foster innovation in infrastructure, promoting a sustainable and inclusive industrial evolution. As the IoT revolutionizes our interconnected future, I am confident that the synergy between RL and IoT will pave the way for systems that are efficient, responsive, resilient, and secure, laying the foundation for a truly interconnected and sustainable world.

1. https://www.coventry.ac.uk/research/research-opportunities/research-students/research-studentships/using-wearable-sensors-for-analysing-awkward-postures-in-construction-workers-coventry-led/
2. https://www.coventry.ac.uk/research/research-opportunities/research-students/research-studentships/using-computer-vision-technologies-for-analysing-awkward-postures-in-construction-workers/
3. https://www.coventry.ac.uk/research/research-opportunities/research-students/research-studentships/ai-iost-artificial-intelligence-towards-reliable-resilient-and-timely-internet-of-space-things/

1. Ihsan Ul Haq (https://pureportal.coventry.ac.uk/en/persons/ihsan-ul-haq)
2. Levi

Resilient Machine Learning: Advancement, Barriers, and Opportunities in the Nuclear Industry Khadka, A., Sthapit, S., Epiphaniou, G. & Maple, C., Sept 2024, In: ACM Computing Surveys. 56, 9, 29 p., 224.