Research Interests
- Generative AI
- Large Language Models (LLMs)
- AI-driven Cybersecurity
- Deep Learning
- Agentic AI
PhD Student | AI-driven Cybersecurity Researcher
PhD student in Computing at Queen’s University, researching AI-driven cybersecurity for cyber-physical systems using generative AI and deep neural networks, with applications in connected vehicles/Internet of Vehicles.
I am a PhD student in Computing specializing in AI-driven cybersecurity. My research focuses on strengthening the security of cyber-physical systems through advanced AI techniques such as generative AI and deep neural networks. Although connected vehicles/Internet of Vehicles are current application areas, my work broadly addresses security challenges across diverse cyber-physical systems.
Before starting my PhD, I completed my MSc in Computing at Queen's University after more than five years of industry experience across software engineering roles.
Sep 2025 – Present
Sep 2024 – Aug 2025 | CGPA: 4.24/4.30
Sep 2015 – Aug 2019 | CGPA: 3.90/4.00
2025
The 2025 IEEE COMPSAC Conference, Toronto
Read Publication2024
IEEE Global Communications Conference (GLOBECOM) 2024
Read Publication2022
HardwareX
Read Publication2021
International Conference on Biomedical and Bioinformatics Engineering
Read Publication2025
Master of Science Thesis, Queen's University
Read Thesis2026
arXiv preprint, arXiv:2601.06937
Read Preprint2026
TechRxiv preprint
Read PreprintHead Teaching Assistant
Assisted designing the labs with the instructor, conducted lab sessions in coordination with the instructor, addressed student questions, and coordinated with fellow teaching assistants.
Teaching Assistant
Mentored project teams, provided implementation guidance, and supported evaluation of deliverables and presentations.
Head Teaching Assistant
Designed assignments with instructor collaboration, coordinated grading, and supported students with coursework and exams.
Head Teaching Assistant
Assisted assignment design, coordinated TA workflows, and supported student learning in operating systems.
Head Teaching Assistant
Supported assignment development, grading, exam proctoring, and student communication.
Python, JavaScript, Java, Kotlin, PHP, C, C++
ML implementation, model training and evaluation, ML pipelines, LLM application development
Full-stack web/mobile/desktop development, scalable system design, Agile, Git, software testing & SQA
AWS, DigitalOcean, Docker
MySQL, PostgreSQL, SQLite, MongoDB, Firebase
Arduino, ESP8266, sensor integration, Figma
Open to collaborations in AI research, LLM applications, and software engineering opportunities.