Passionate about Artificial Intelligence, Quantum Machine Learning, backend development, and software engineering.
Currently focused on Large Language Models (LLMs), Quantum Machine Learning, Variational Quantum Circuits (VQC), Quantum Kernel methods, and applied AI research.
Software Engineering student at INATEL with interests in Artificial Intelligence, Machine Learning, Quantum Computing, backend development, and cloud technologies. Experience developing projects using Python, Java, Docker, AWS, REST APIs, Jenkins, and computer vision frameworks such as YOLOv5. Currently exploring Quantum Machine Learning, LLM applications, automation systems, CI/CD pipelines, and scalable software architectures.
Experiments involving Variational Quantum Circuits (VQC), Quantum Kernels, and hybrid quantum-classical models.
Full-stack vehicle comparison platform built with React, Node.js, MySQL, and Docker Compose.
Java-based management system featuring layered architecture, automated testing, and Jenkins CI/CD pipeline.
