Researcher in AI-Driven Test Automation and Intelligent Quality Engineering
The research focuses on applying artificial intelligence and machine learning to improve software testing and quality engineering. Traditional testing approaches rely heavily on manual processes and static automation frameworks. This research explores how predictive analytics, machine learning models, and autonomous testing systems can significantly improve testing efficiency and reliability.
The objective is to build intelligent quality engineering platforms capable of predicting software defects, generating automated test cases, and continuously improving testing strategies based on repository analytics and system behavior patterns.