Final-year Practical Computer Science student at the University of Gdańsk. I primarily work with Java and Spring Boot in my everyday tasks, while also building experience with Python, TypeScript and Angular. Currently involved in a students' academic circle project — L2B2 Platform — where I lead as Backend Tech Lead (codebase is private, hosted on GitLab). I use AI tools such as Claude to optimize my work and improve productivity. I am looking for place to grow as a developer.

📫 How to reach me: mikolajkalejta@gmail.com

A long-term mobile application aimed at simplifying the search for short-term and freelance jobs through a user-friendly and transparent platform. Co-created the application architecture from concept stage, designed and developed the backend with Spring Boot, and built the database model with scalability in mind. I was fully responsible for the admin panel, implemented as a submodule using TypeScript with Angular.

A web-based electronic school gradebook built as a monolithic application with separated domain modules (grades, attendance, timetable, messages, etc.). The system uses Docker and Kubernetes for containerized deployment, Keycloak for authentication, and communicates through REST, RabbitMQ and Redis across 11 independently built services.

A machine learning project developed for a Computational Intelligence university course, predicting chess game outcomes (white wins, black wins, draw) from Lichess game data. Implements and compares four models — Neural Network (Keras), Random Forest, XGBoost, and KNN — with GridSearchCV hyperparameter tuning, achieving 86.3% test accuracy with XGBoost. Also includes Apriori-based association rules mining to discover patterns between chess openings and game outcomes.