I am completing my PhD in Computer Science at Trinity College Dublin, where my research has focused on mathematics‑driven quantitative methods, foundational machine learning, generative AI and natural‑language processing (NLP) with the motivation of making conversational agents more human like. My doctoral work produced a highly scalable, compute/cost effective and most importantly, secure inference infrastructure for running multi-adapter LLM systems in parallel asynchronously. One of the key advantage of this approach is to run Agentic AI Systems locally on premise with reduced memory footprint up to 90% . Prior to my PhD, I gained entrepreneurial experience developing misinformation analysis tools like NewsChase and Fictometer, alongside recent research mitigating bias in Large Language Models – a crucial step towards a fairer and more trustworthy AI landscape. These experiences gave me a first‑hand understanding of the commercial lifecycle of data‑driven products, from ideation and MVP delivery to user acquisition and iterative refinement.
Last updated: 13 July 2026
Research themes
Runs AI inference locally by optimising GPU memory, letting organisations deploy multi-agent systems without cloud API costs or data leaving the building.
Trinity College Dublin
Lead: Dr. Mohammed Rameez Qureshi
Data Security, Privacy & GovernanceLet's discuss how The ARC Hub for ICT can help accelerate your digital transformation initiatives and bring your innovative ideas to life.