Hey, I'm Reagan Dias|

Reagan Dias

About

I’m a Software Engineer who cares deeply about thoughtful design and building systems that feel intentional.

I enjoy working across the stack and exploring how AI can enhance real products — not just demos.

Career Journey

The work that shaped how I build: systems, automation, product thinking, and shipping responsibly.

Sep 2021 — 2025University of Reading

BSc Computer Science (Industrial Year)

First-class foundations, shipped systems work, and a dissertation built for scale.

SystemsMLCloudResearch
  • First Class Honours (83%).
  • Dissertation: scalable image-to-image retrieval (FAISS, FastAPI, Docker, AWS ECS).
  • Won the Sullivan Prize for best Computer Science Project (publication underway).
Jul 2023 — Jul 2024Eli Lilly and Company — Arlington, Bracknell

System Analyst (Industrial Year)

Learned how real teams run: requirements, operations, and automation that sticks.

AutomationOpsDashboards
Jul 2024 — Jul 2025Eli Lilly and Company — Lilly House, Basingstoke

Business Analyst

Turned messy work into repeatable systems — measurable savings, less manual effort, better UX.

DataAutomationPower BI
Sep 2025 — PresentEli Lilly and Company — Lilly, Basingstoke

Software Engineer

Owned product experiences end-to-end — UX, frontend architecture, and cloud deployment.

FrontendAWSLLMsGraphRAG

Featured Work

Selected projects where design, engineering, and intent come together.

PRISM — Open Source Visual Search

PRISM is a scalable image-to-image search system designed for e-commerce, enabling users to find visually similar products using a single uploaded image.

PythonPyTorchCLIPResNet50FAISSFastAPIDockerAWS (ECS, S3, IAM, ALB)ReactUvicornLocust

Phi.ai

An AI decision layer for Web3 that combines persistent personas, seeded predictions, and on-chain verification to create trustworthy autonomous agents.

Next.jsReactTailwindCSSPythonSpoonOSOpenAI APINeo N3NeoFS
liver disease preview

Liver Disease Prediction

A predictive machine learning model built to identify liver disease risk from clinical datasets, exploring preprocessing, feature engineering, and model performance trade-offs.

PythonPandasNumPyScikit-learnXGBoostMatplotlibSeabornJupyter Notebook