Third-year Computer Science student at Politehnica University of Bucharest.
I work mostly with Java and Python — building web applications with Spring Boot and training ML models with scikit-learn and TensorFlow. Lately I've been focused on integrating ML pipelines into full-stack systems via Flask REST APIs.
- Emotional Monitoring App — full-stack web app with Spring Boot + Flask + SQL Server. Uses Ridge Regression (R²=0.91) for mood score prediction and Naive Bayes (78.5% accuracy) for day classification.
- AI vs Human Text Classification — Naive Bayes vs SVM with TF-IDF on a Kaggle dataset of 2,000 samples. Naive Bayes: 92.75% accuracy.
- Hyperspectral Image Classification — 3D CNN with TensorFlow/Keras on 19×19×48 patches. Macro F1: 0.6080.
- Exam & Project Management — Spring Boot — role-based platform with Spring Security, JPA/Hibernate and REST endpoints.
- Exam & Project Management — Java — desktop app with Java Swing + JDBC, 7 relational tables and complex SQL subqueries.
- Product Catalog — Full Stack — Node.js + Express REST API with vanilla JS frontend and SQL transactions.
Languages: Java, Python, C++, C, JavaScript
ML/AI: scikit-learn, TensorFlow, Ridge Regression, Naive Bayes, SVM
Backend: Spring Boot, Flask, Node.js, REST APIs, JPA/Hibernate
Databases: SQL Server, MySQL
Tools: GitHub, Maven, MATLAB
- Finishing 3rd year at UPB
- Looking for a summer internship in ML, backend or full-stack
- Registered for the 2026 Google Student AI Hackathon at UPB
- LinkedIn: Anna Halca
- Email: ahalca4@gmail.com