I am a Software Engineer at OpenMined Foundation passionate about building secure, privacy-preserving AI systems. Collaborated with third-party clients includeing Reddit, Anthropic and the UK AI Security Institute on cutting-edge AI evaluation frameworks.
- Expertise: Privacy-Preserving AI, Cybersecurity, Full-Stack Development
- Education: MSc Biomedical Engineering (Distinction) - University of Hull
- Certifications: CISSP, PMP, AWS Solutions Architect
- Location: London, UK
- Currently: Contributing to Node.js Core
Software Engineer @ OpenMined Foundation (Jan 2024 - Present)
- Enhanced security by refactoring Python encryption algorithms for Syft toolkit
- Developed Python SDK for LLM integration, reducing deployment costs
- Drove 4.5k+ monthly downloads through automated documentation
- Piloting secure enclaves with Anthropic & UK AI Security Institute
- 70% reduction in bugs via TypeScript dependency tracking
- 20% reduction in auth support tickets through Okta migration
- 3x platform growth using PyTorch dynamic pricing models
- 70% reduction in phishing click-through rates
Node.js WebSocket Client (Jan 2025 - Present)
- Contributing to Node.js WebSocket client documentation
- Enabling built-in low-latency, real-time data exchange
Syft Toolkit Documentation (Dec 2022 - Feb 2023)
- Maintaining dynamic Sphinx theme with native browser APIs
- 200+ monthly downloads and growing
- CISSP - Certified Information Systems Security Professional (2025-2028)
- PMP - Project Management Professional (2024-2027)
- AWS Solutions Architect - Certified (2021-2024)
- GDPR - General Data Protection Regulation (2021-Present)
- Azure Fundamentals - Microsoft Certified (2021-Present)
NeurIPS 2025 (Submitted)
"Attribution-Based Control: Unlocking New Data for AI Without Compromising Copyright or Privacy"
Co-authors: A. Trask, L. Strahm, D. Buckley, et al.
OpenMined 2024 (Published)
"Secure Enclaves for AI Evaluation: A pilot experiment conducted by OpenMined, in partnership with the UK AI Safety Institute (AISI) and Anthropic."
Co-authors: A. Trask, L. Strahm, D. Buckley, et al.
"Building secure, privacy-preserving AI systems that unlock innovation without compromising trust."