Luis Felipe Freitas

Developed and optimized prompt-based pipelines for dietary meal plans, ensuring adherence to user dietary requirements. Designed context-sensitive prompts and created automated validation processes, achieving a 70% decrease in manual review requirements. Collaborated with teams to integrate solutions into production.

Designed and deployed computer vision models using YOLO v7 for object detection, focusing on surgical instruments. Conducted feature engineering and collaborated with teams to implement data-driven solutions.

Analyzed data from multiple APIs to generate reports for investors and designed models to detect anomalies in cryptocurrency transactions. Implemented machine learning models for real-time inference on AWS.

Partnered with various professionals to optimize business processes using AI. Influenced key decisions and trained object detection models, achieving high accuracy metrics.

Developed teaching materials and instructed courses on machine learning and business-focused artificial intelligence, utilizing practical cases and examples.

Performed risk assessments in IT, managed IT projects, and provided AI/ML solutions to optimize business processes. Collaborated with engineers to create business solutions.

Pursued a degree in Information Security, covering topics such as cybersecurity, data protection, and risk management in information systems.

Studied Communication Network Engineering, focusing on the principles of communication systems, network protocols, and data transmission techniques.