Research & Innovation
PhD-level foundations and delivery leadership across funded research programmes, high-performance computing, and applied systems engineering.
Foundations
Academic training and applied research experience
- PhD: Aeronautical Engineering — Helicopter Aerodynamics (Queen Mary, University of London)
- UK Ministry of Defence: 4 years post-PhD research on helicopter aerodynamics (results delivered under appropriate constraints)
- HPC & CFD: Longstanding work on parallel CFD solvers, performance optimisation, and distributed compute architectures
Note: For sensitive or restricted programmes, Symban describes scope and outcomes at an appropriate level and avoids confidential detail.
Funded programmes & consortia
Initiation, proposal leadership, technical architecture, and delivery governance
FLOWGRID (European Commission, 2004)
Initiated and led a European consortium of companies and universities to develop a distributed grid-based platform for running CFD applications. The consortium was awarded €1.1m in funding, with Symban providing technical leadership and project management.
PASHA (EU programme, 1998)
Project managed a European-funded programme focused on high-performance systems and networking, coordinating delivery across partners and ensuring technical and programme governance.
Academic & industry collaboration
Experience working across university and industry contexts: aligning research objectives with engineering constraints, delivering usable platforms, and supporting dissemination and adoption.
How Symban works in research & academic contexts
A practical delivery model for high-trust programmes
Translate research into an executable plan
Turn research goals into a delivery plan with clear milestones, success criteria, datasets, and evaluation methods. Establish a credible path from prototype to adoption.
Engineer for reproducibility
Prioritise reproducible compute: containers, versioned pipelines, documented assumptions, automated testing, and controlled environments—essential for research credibility and repeatability.
Deliver governance without bureaucracy
Provide pragmatic governance: work-package coordination, reporting cadence, RAID discipline, and stakeholder alignment—lightweight enough to move fast, strong enough to reduce programme risk.
Research & engineering themes
Areas of depth that connect research to production delivery
- High-performance computing: parallelisation, profiling, scalability, schedulers, and compute automation
- Scientific software engineering: reliability, validation, reproducibility, and data pipelines for scientific outputs
- Distributed computing: architectures spanning grid, cluster, and hybrid cloud compute
- Applied AI tooling: using modern AI/LLM methods to support knowledge work and accelerate workflows where appropriate
Related pages: Selected outputs are listed in Publications. Delivery examples can be found in Case studies, with summarised outcomes in Achievements.