Monty Dean

Independent AI Developer

Reading, RG6
07450700354

I am an independent AI developer and researcher, combining a strong foundation in Mathematics and Computer Science with hands-on expertise in building and deploying practical machine learning models. I specialize in making AI accessible and useful—whether optimizing diagnostic summarization tools or designing intuitive AI solutions for underserved demographics, such as elderly-accessible ordering systems.

Certified in Azure AI Fundamentals (AI-900), I am seeking a professional opportunity where I can apply my analytical skills, rapid learning capability, and proactive problem-solving mindset to build impactful, real-world AI applications.

Mathematics Computer Science Azure AI Fundamentals Machine Learning Model Fine-Tuning Customer Service Active Problem Solving Initiative & Autonomy
BSc Mathematics with Computer Science (1 Year Completed) 2024 - 2025
University of Reading

Completed foundational coursework in mathematics, programming, and computer systems before pivoting to full-time independent AI research and development.

A Levels 2022 - 2024
Bluecoat Sixth Form (Nottingham)

Mathematics (A), Further Mathematics (B), Computer Science (B)

GCSEs 2017 - 2022
South Nottinghamshire Academy

Mathematics [9], Computer Science [8], Combined Science [6-6], Geography [6], English [6], English Literature [5], Music [Distinction]

Call Agent Mar 2023 – Nov 2023
MPL Contact (now merged with Answer4u)
  • Answered the phone for a variety of companies on their behalf
  • Booked appointments for clients
  • Called and monitored the status of engineers for emergency situations
  • Handled angry or challenging customer scenarios with professionalism
Call Center Agent Summer 2022 (1 Month)
Answer4u
  • Answered the phone for a variety of client companies
  • Passed on detailed, accurate messages
  • Handled customer complaints effectively
  • Worked efficiently under time-sensitive call conditions

Radiology AI Summarizer

A 2.97 GB clinical language model fine-tuned to compress dense findings into precise impressions on CPU (+156% ROUGE accuracy vs base).

Spiral Data Classifier

A PyTorch-trained neural network demonstrating the power of adaptive optimizers (Adam vs SGD) with an interactive 2D canvas boundary plotter.