Hello, I'm Ash.
I run the Applied AI team for the markets business of a world-leading financial institution, working at the intersection of complex market structure, large-scale systems, and real operational change. My work focuses on turning advanced machine learning into durable capabilities that reshape how large organisations function, not just how they experiment.
Alongside setting strategy and building teams, I remain deeply involved in the technical work. I still design architectures, review models, and write code. I believe credibility in this field comes from staying close to the systems themselves, understanding their edge cases and failure modes, and being accountable for what happens after deployment.
My background is deliberately interdisciplinary. I began in biomedical science, moved through bio-inspired computing, and completed a PhD focused on machine learning for algorithmic trade execution. That path shaped how I think about markets — as complex, adaptive systems where data, incentives, and human behaviour interact in non-obvious ways.
I have led AI teams inside global financial institutions and worked across a number of hedge funds and investment firms, helping design and deploy machine learning in high-stakes, production environments. My research has been published in peer-reviewed venues, spanning market microstructure, high-frequency trading, and ensemble learning. Much of my most meaningful work, however, exists quietly inside production systems, operating at scale every day.
I am motivated by building things that hold up in the real world. Scalable platforms, high-trust teams, and AI systems that earn their place by running in production. This site is where I share ideas, systems thinking, and lessons learned from building and operating AI where results are the only measure that matters.