Engineering AI Autonomous Systems

We have developed methodologies and techniques for developing and maintaining autonomous system.


The rise of Artificial Intelligence (AI), empowered by the growth and availability of big data, breakthroughs in AI algorithms (e.g. deep learning), and significantly increased computational power, is potentially a game changer in fighting against software vulnerabilities. We are working towards AI-powered automated solutions which: (1) instantaneously detect vulnerability threats while code is being written and alert the software engineers of those threats; and (2) recommend patches to fix those vulnerabilities. Through this novel approach of tackling vulnerabilities early in the software lifecycle, this project will prevent vulnerabilities from being injected in the code at the very first entry point, thus saving the significant cost increase later.

  1. Trust autonomous systems:

  1. Methodologies for engineering autonomous multi-agent systems:

  1. Evolving and maintaining autonomous multi-agent systems: We have developed AI deep learning models (Tree-LSTM and CNN based) for predicting defects in large codebases and also in code changes (e.g. commits).