Research
Research at the intersection of artificial intelligence and cybersecurity — intrusion detection, cross-platform malware analysis, privacy-preserving learning and intelligent healthcare.
FedQDFU: Non-IID Federated Quantum Learning for Diabetic Foot Ulcer Classification from Deep Image Features
Ph.D. Student in Electrical Engineering and Computer Science · Texas A&M University–Kingsville
Publications are linked to a theme when their title, keywords or assigned research area match it.
Protecting systems, networks and data from attacks, intrusion and misuse.
Identifying malicious activity in network traffic and system behaviour.
Detecting and characterising malicious software across Windows and Android.
1 related publication →Training models collaboratively without centralising raw data.
Machine learning that limits the exposure of sensitive or personal data.
Making model decisions transparent and interpretable to people.
Machine learning for diagnosis, screening and health monitoring.
Learning from images and video for recognition and detection tasks.
Learning over graph-structured data such as control-flow graphs.
Machine learning methods that draw on quantum computing.
Connected sensing and deep learning for farming, food and environmental monitoring.
OngoingFederated Learning · V2X Security
Vehicle-to-Everything (V2X) communication supports cooperative mobility and safety applications, but a single Sybil adversary can emulate multiple vehicles and distort traffic perc...
National Science and Technology Fellowship · Mawlana Bhashani Science and Technology University, Bangladesh
Amount: Approximately $500
Supervised by Professor Dr. Mohammad Motiur Rahman
Associated publication: Sustainability, MDPI (Published)
University Grant Commission (UGC), Bangladesh
Amount: Approximately $2,500
Supervised by Professor Dr. Mohammad Motiur Rahman
Associated publication: IEEE Transactions on Artificial Intelligence & Heliyon (Published)