Developing and maintaining an ERP system, primarily using C#, .NET, TypeScript, JavaScript, and MongoDB, contributing significantly to performance and scalability for large data volumes. ● Implemented significant performance improvements in large-scale data flows and operations, optimizing for high-volume data processing. ● Drastically reduced processing time for a critical C#/.NET routine from 50 minutes to under 2 seconds through memory usage optimization, bulk operations, HashSet utilization, and other targeted adjustments. ● Contributed to system modernization by migrating legacy components (ASPX, JavaScript, .NET Framework) to modern technologies (Angular, TypeScript, .NET Core).

Developing a gamified platform for cybersecurity education using Next.js, Express, React, and Firebase, featuring AI integration and a vector database (Pinecone). ● Integrated SOTA AI models using Retrieval Augmented Generation (RAG) to provide context-aware, factual responses based on RNP partner data, minimizing hallucinations. ● Engineered and deployed applications in a Linux (Debian) environment, configuring web servers (Apache) and reverse proxies. ● Created Rest APIs for seamless communication between the applications’s frontend and backend systems. ● Version 1 of this tool has been approved for open-sourcing and will be released as soon as I complete the accompanying white paper.

Conducted applied research in Artificial Intelligence for intrusion detection in CAN-type intravehicular networks, focusing on explainability and data analysis. ● Developed Python-based algorithms for feature selection and processing large datasets, crucial for effective AI/ML model training. ● Developed IWSHAP, an open-source CLI tool for feature selection that combines traditional methods (e.g., IWSS) with SHAP's ranking and explainability, improving performance and providing clearer insights into feature importance. ● Created, trained, and evaluated multiple Machine Learning models (Scikit Learn, Keras) for attack detection in different datasets. ● Presented research findings at SBSeg 2024, Brazil's leading cybersecurity symposium (recognized among top papers).