I build agentic AI systems that know their own limits. My work focuses on the gap between autonomous capability and institutional accountability — designing architectures where AI agents can be stopped, audited, and corrected when they behave unexpectedly. I'm a 3rd-year IT student at the Islamic University of Madinah and have published 15 peer-reviewed papers on AI governance, adversarial robustness, and constrained multi-agent systems.
I study how to make autonomous AI systems fail safely: designing governance architectures that prevent unintended actions before they propagate through real-world infrastructure.
Current Research Frontier
Autonomous Safety Governance
Safety-Critical Multi-Agent Systems
"Investigating cryptographic trust-anchors and constrained reasoning for large-scale agentic deployments."
I study how to make autonomous AI systems fail safely: designing governance architectures that prevent unintended actions before they propagate through real-world infrastructure.
My work addresses the alignment problem in deployed agentic systems — exploring how we can build autonomous pipelines that remain safe and governable when exposed to adversarial inputs, distributional shift, or misaligned incentives. I approach this through the intersection of safety engineering, formal governance frameworks, and empirical failure-mode analysis.
Toqeer Ali Syed, Ali Akarma, Muhammad Tayyab Naqash, Danial Hameed, Shahid Kamal, Antonio Formisano
Ali Akarma, Toqeer Ali Syed, Salman Jan, Hammad Muneer, Abdul Khadar Jilani
Ali Akarma, Toqeer Ali Syed, Abdul Khadar Jilani, Salman Jan, Hammad Muneer, Muazzam A. Khan, Changli Yu