Introductions
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Who I Am¶
An experienced technical consultant specialising in AI Solutions and Generative AI implementation, with an academic AI background. A Professional Member of the Institute of Analysts and Programmers holding an dual honours degree in Artificial Intelligence and Computer Science from the Russell Group University of Birmingham.
I help teams, companies, and organisations:
- Build AI prototypes and solutions
- Solve problems using AI
- Technical reviews and evaluation
- Implement AI in a future-proof manner with upgrades in mind
- Advise on state-of-the-art AI tools and knowledge
I have carried out technical reviews of AI Book Publications for Springer Apress. Also, technical reviews of Edge AI University course material and lessons as part of a Global Education Project to help educate students in EdgeAI with Imagination Technologies, Madrid University and Peking University.
Recognition¶
- Featured on fast.ai SolveIT homepage as testimonial for the SolveIt course
- Writing shared by Eric Ries (The Lean Startup) on Hacker News as "one of my favorite writeups"
- Technical Reviewer for Springer/Apress "PyTorch Recipes" (2nd edition)
- Technical Reviewer for Imagination Technologies Global Edge AI curriculum (adopted by universities worldwide)
- Presented at International Working Dog Conference 2025 on AI robotics solutions for working dogs
- Topped Jeremy Howard's Fashion-MNIST leaderboard in every epoch category (5, 20, 50 epochs) with a non-pretrained model
- Perceptual Latent Loss research (June 2023) — 18 months before Meta's similar approach in "Boosting Latent Diffusion with Perceptual Objectives"
Services¶
I help teams, companies, and organisations:
- Commercial AI Research: Feasibility studies, SOTA evaluation, architecture design for specific constraints, proof-of-concept development
- RAG Systems: Hybrid vector/BM25 search, reranking, embedding model selection, text/tabular/image retrieval
- Agents and Automation: Multi-agent systems, LangGraph, LangChain, human-in-the-loop workflows
- LLM & VLM Implementation: OpenAI, Anthropic, Gemini, Llama, Qwen; fine-tuning, LoRA training, synthetic data generation
- Quality & Evaluation: Hallucination reduction, LLM-as-judge, confidence scoring, regression testing
- Computer Vision: Custom model architecture design, training, super resolution, edge deployment, INT8 quantisation
- Image Generation: Diffusion models, Stable Diffusion, Flux, LoRA training, generative image editing
- Prompt Engineering: Effective prompting for language and image models
Background¶
- AI degree from University of Birmingham (2000) with cited thesis on evolutionary image processing
- Completed every fast.ai course from 2016-2022
- One of the first cohort of 1000 SolveIt students
- First neural network trained in 1999 on census data
- First NLP work using Prolog in 1998
Skills and technologies¶
- Prompt engineering for Language Models
- LLMs, SLMs, VLMs, RLMs
- RAG, advanced
- AI Tools: LangChain and LlamaIndex
- AI Agent frameworks: LangGraph, Smolagents, LlamaIndex Workflows
- PyTorch, Python, .Net, C#
- Quantisation of Edge AI models and testing models running on FPGA implementations of Neural Network Accelerators
- Synthetic data generation
Testimonials¶
"Chris joined Imagination to consult in the area of deep learning, specifically super-resolution. He arrived with comprehensive knowledge of existing networks and their capabilities... Chris was able to communicate effectively with research staff and navigate our engineering infrastructure to produce results quickly. I wouldn't hesitate to engage Chris again... He is professional, articulate and a pleasure to work with."
— Vice President, Compute Software (Technology Office), Imagination Technologies
"Chris is one of the most competent, most imaginative problem-solvers I've come across. He's unafraid to tackle difficult technical matters... He's obviously very intelligent and he keeps up-to-speed with latest technologies."
— Solution Architect, Global Technology Services Company
Production Impact¶
| Project | Result |
|---|---|
| Multi-locale Translation Pipeline | Days/weeks → hours/minutes across locales including Polish, Korean, Arabic |
| Conversational AI System | 76% answer rate across 6,400+ queries |
| RAG Content Generation | 10x content scaling (200 → 2,000+ Q&A pairs) |
| Edge AI Super Resolution | 30+ fps real-time performance on neural network accelerator hardware with integer quantisation |
Research Interests¶
Currently collaborating with the former Head of Breeding at Guide Dogs UK on AI-powered dog behaviour assessment and exploring robotic quadrupeds as assistive technology — presented at the International Working Dog Conference 2025.