I am a Software & Data Engineer based in Belgrade, passionate about bnuilding robust backend systems and engineering scalable data pipelines as well as machine learning algorithms in practice and research. Currently, I serve as a Teaching Associate at Singidunum University, where I work and collaborate with professors in many fields of Software Engineering through academic research and course administration.
- 🔭 I’m currently working on: Real-time Intrusion Detection & Prevention systems with ML Algorithms.
- 🌱 I’m currently learning: Advanced Microservices in Spring Boot.
- 💡 I have a knack for: Bridging the gap between complex mathematical theory (AI/ML) and production-grade software development and engineering.
| Domain | Technologies |
|---|---|
| Backend Engineering | Java (Spring Boot, Hibernate), Python, RESTful APIs, Microservices, JUnit |
| Data & AI/ML | PySpark, PyTorch, TensorFlow, OpenCV, Pandas, Scikit-learn |
| Cloud & DevOps | AWS (S3, Lambda), Azure, Docker, Kubernetes, Git |
| Databases | MySQL, PostgreSQL, Oracle, MongoDB (NoSQL) |
Research presented at Sinteza 2025 International Scientific Conference.
- The Challenge: Improving brain tumor segmentation accuracy in MRI scans.
- The Solution: Conducted research on six Adam optimizer variants using a hybrid deep learning model on the large-scale BraTS 2020 dataset.
- Tech Stack: Python, PyTorch, Pandas, Deep Learning.
- Overview: A complete ETL pipeline designed to ingest, process, and analyze massive volumes of historical F1 telemetry data.
- Impact: Enabled complex SQL querying for in-depth race analysis and reporting.
- Tech Stack: Python, PySpark, AWS Cloud, SQL.
- Overview: A real-time network security system that utilizes machine learning to "sniff out" malicious threats better than standard rule-based firewalls.
- Methodology: Processed large-scale telemetry data (UNSW-NB15) to train models for identifying network anomalies.
- Tech Stack: Scikit-learn, PySpark MLlib, Python.
- Overview: Architected the core driver-rider matching algorithm and real-time payment processing for a ride-hailing platform.
- Key Achievement: Implemented Spring Security for robust authentication and optimized Oracle DB queries for rapid matching.
- Tech Stack: Java, Spring Boot, Spring Data JPA, Oracle DB.
P.S I have a lot of projects I work on... Feel free to explore my jungle of repositories
- B.S. Software & Data Engineering - Singidunum University (2021-2025)
- Cisco CCNA | IBM Rational Software Architect | RedHat OS System Admin
Let's connect and build something incredible! 💫🌠