Areas of expertise
I help organisations turn AI research and emerging technology ideas into practical solutions that deliver measurable real-world impact.
- Promising AI concepts that stall between experimentation and deployment
- Computer vision or deep learning models that never make it into production
- Data science work that fails to improve decision-making at scale
- LLM projects that lack the structure to automate complex tasks reliably
- Research challenges where the gap between theory and application blocks progress
I come in, validate what is actually possible, and build the path from prototype to deployed solution that creates lasting value.
About Me
I am a Lead AI/ML Engineer and PhD-qualified researcher with deep expertise in computer vision, deep learning, LLMs, and data science.
I work at the intersection of cutting-edge research and real-world deployment - helping organisations move from experimentation to solutions that actually work in production environments.
I help clients turn raw data, AI ideas, and research challenges into validated systems that automate complex tasks, sharpen decision-making, and deliver measurable impact. Whether you are a startup finding your technical footing or an established organisation scaling AI capability, I bridge the gap between what is possible and what is deployable.
My PhD focused on state-of-the-art deep learning for digital pathology and cancer grading. I have published peer-reviewed research in Scientific Reports, Cancers, and SPIE Medical Imaging, and applied AI across healthcare, pharma, veterinary medicine, and wearable technologies with startups, research institutions, and multinationals.