DIMITRIOS KAMPOURIDIS

Deployed and maintained Linux and Windows servers and monitoring systems to support mission-critical operations, ensuring high uptime and rapid incident response in secure, time-sensitive conditions.

Developed XGBoost and logistic regression models on historical sports betting data to generate bet-selection signals and containerized five end-to-end ML pipelines with Docker to standardize experimentation.

Designed and implemented a Python Monte Carlo race simulation engine using OpenF1 telemetry and ran 5,000+ simulations per strategy to evaluate pit-stop plans; built a Flask web dashboard and Dockerized the system for reproducible decision-support experiments.

Built a Blazor web application integrated with an Azure ML-hosted regression model to forecast car prices and deployed the forecasting pipeline to Azure for real-time user predictions.

Optimized Java/Swing-based memory-training games for elderly users and collaborated with researchers to improve usability and accessibility for non-technical older adults.

Activities and societies: MSc thesis: Formula One Race Strategy Simulator; built Python simulation engine using OpenF1 telemetry, ran 5,000+ Monte Carlo simulations per strategy, and deployed a Flask web dashboard in Docker.

MSc in Data Science and Artificial Intelligence with a thesis developing a Formula One race strategy simulator using Monte Carlo simulation and a Flask+Docker deployment for interactive strategy analysis.

Activities and societies: Final year project: Auto Price Forecasting Web App (Blazor + Azure ML); developed and optimized Java/Swing memory-training games for Alzheimer’s project.

Bachelor of Science in Computer Science with a final-year project building an Auto Price Forecasting web app integrating Azure ML and a Blazor frontend.