About
Al Brown leads Cassi’s R&D working at the frontier of AI and the intersection of multiple disciplines, where every programme directly contributes to Cassi’s products and services today, while progressing towards new approaches to optimally efficient knowledge acquisition architectures tomorrow. A former Royal Engineer and physics graduate, he brings two decades of engineering leadership, operational command and defence R&D to get the best out of everyone on his team – focused on the mission, while making sure they have fun along the way.
Al was among the first in the British Army to champion AI for command decision support, later authoring the UK Ministry of Defence’s Human‑Machine Teaming concept (JCN 1/18).
As Chief of the General Staff Scholar and Visiting Research Fellow at Oxford, he researched optimisation of multi‑agent human–machine teams and model architectures for decision‑making. He subsequently served as Director of Neurosymbolic AI at Fujitsu’s Centre for Cognitive & Advanced Technologies, where he led ML developers and academic partners to deliver forensically defensible data‑query systems and edge machine‑vision, convening early government–frontier‑lab dialogues on emerging risks from LLMs. He has led on ML technical due diligence while at Fujitsu, as well as advising on product-market fit – giving him an eye not only for what works, but what sells.
Al’s technical focus spans Bayesian modelling, value‑of‑information analysis and dynamic resource allocation for intelligence problems. He is an advocate of “better priors” and active‑inference‑inspired design, drawing on Friston’s Free Energy principle to couple statistical learning with accountable reasoning. He is an Associate Fellow at RUSI, a lecturer at leading institutes, and has contributed UK expertise at the United Nations on autonomy and AI.
At Cassi he hires people who care about two outcomes: measurable impact in the field and contributing maximally to the team. If you want your research to ship, not shelve – have fun and improve along the way – you’ll fit.