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Fall 2020·Dr. Junaid Akram

Supervised Student Project

CompletedFall 2020BS Software Engineering

Analysis and Detection of Fraudulent Transactions Using PaySim Simulator

Supervised student project implementing machine learning algorithms to detect synthetic financial fraud signals generated by the PaySim simulator.

Fraud DetectionPaySim SimulatorMachine Learning
Students

Ouyang NingJing

Supervision

Dr. Junaid AkramLead Supervisor

Institution

Financial Fraud ResearchXiamen University Malaysia

Supervised Projects Portfolio

More Supervised Projects

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Full-Stack & Systems

MegiLance — AI and Blockchain-Powered Freelancing Platform

A supervised final-year engineering development project combining a full-stack freelancing marketplace with AI decision assistance and blockchain payment escrow.

Ghulam Mujtaba, Muhammad Waqar Ul MulkView Case Study
Vulnerability & Security

Software Vulnerability Detection using LLM Model

A running research project leveraging Large Language Models (LLMs) to detect complex software vulnerabilities in source code through fine-tuning and AST-based prompt engineering.

Syed Muhammad Irtaza Shahid, Muhammad Waleed, Muhammad Muneeb AzharView Case Study
Vulnerability & Security

Token-Based Semantic Code Clone Detection

A running software security project building a scalable token-based semantic code clone detection platform to capture Type-3 and Type-4 clones across large open-source repositories.

Ali Muhammad, Ali Murtaza, Hafiz Muhammad Shams ul HudaView Case Study