Machine Learning-Based Fileless Malware Threats Analysis for the Detection of Cybersecurity Attacks Based on Memory Forensics Conducted an in-depth study on the challenges of detecting fileless malware, which bypasses traditional detection mechanisms by hiding in system memory (RAM) and leaving minimal traces on the file system.

Bachelor of Computer Science National University of Computer and Emerging Sciences (FAST) Worked on full-stack development using Angular, Node.js, React.js, Python FastAPI and Langchain. Contributed to the development of a cross-platform React Native app for riders, enhancing the mobile experience on both iOS and Android. Collaborated on improving backend services. Developed a Retrieval-Augmented Generation (RAG) chatbot that extracts data from Confluence and uses it to answer queries within the chatbot.