I am an Applied Informatics student at UJEP with a strong foundation in computer networks and building high-performance, real-time systems. My expertise lies at the intersection of Edge AI, backend architecture, and statistical modeling.

Currently, I am working on my bachelor's thesis focused on an automated traffic monitoring system. By leveraging YOLO models, Hailo-8 AI accelerators, and FastAPI, I’ve engineered a pipeline capable of processing complex visual data with sub-second latency.

Beyond the engineering layer, I am fascinated by how we interpret high-velocity data under uncertainty. I have a deep interest in Quantitative Analysis and Bayesian Statistics, particularly in updating hypothesis probabilities with new evidence and understanding the mechanics of Fat-Tailed distributions in volatile environments like crypto and HFT markets.

I enjoy solving technical challenges where software efficiency meets mathematical intuition. Whether it's optimizing an MQTT data stream or calculating expected values for risk management, I aim for precision and scalability.

Specializations: Edge AI (Raspberry Pi, Hailo-8), Computer Vision (YOLO), Statistical Modeling, Real-time Data Pipelines.

• My Bachelor's Thesis: Developing an automated real-time traffic monitoring system using Computer Vision and Edge AI.
• Project Tech Stack: Raspberry Pi 5, Hailo-8, YOLO, MQTT, PostgreSQL, FastAPI, Python.

• Programming & Backend: Python (FastAPI, Automation, Scripting), C#, PostgreSQL, Git
• Edge & IoT: Raspberry Pi, MQTT, Computer Vision (YOLO)
• Networking & Systems: CCNA (1-3), Linux (Advanced User), Windows Administration

• Expanding my expertise in data processing, edge computing and secure IT infrastructure.
• Actively seeking international internship opportunities.