João Pedro Pereira Santiago

Designing, developing, and deploying ML models for large-scale industrial energy systems, implementing MLOps pipelines and IoT sensor monitoring to optimize energy usage and forecasting.

Developed a deep learning system for Brazilian Sign Language translation, handling keypoint extraction, dataset preparation, model training, and large-scale evaluation using PyTorch and TensorFlow.

Designed and implemented scalable data systems and AI-driven automation, building ETL pipelines, AI-enhanced web scrapers, REST/GraphQL APIs, and containerized deployments with Docker and Kubernetes.

Led a scientific initiation project applying computer vision and ML to assist mobility for visually impaired individuals using YOLO, OpenCV, and embedded device integration for real-time detection.

Collaborated on full-stack development to implement and deploy ML models, integrating Django-based backend with PostgreSQL and real-time industrial sensor data.

Developed ERP systems and integrations using Delphi, C++, SQL, and Python, optimizing databases and implementing payment and stock management solutions.

Designed and implemented KPI dashboards and SQL-based data representations, applying design patterns to ensure efficient, scalable analytics solutions.

Automated and optimized spreadsheets and workflows using Python and Pandas, and developed invoice and resource management software to streamline operations.

Practical and theoretical academic development in software engineering, databases, and distributed systems with hands-on projects.

Completed an advanced FIC course on computer vision techniques including image segmentation, modern object detection methods, and evaluation metrics.

Completed a focused FIC course on database administration covering administration, optimization, and security of relational and NoSQL databases.

Completed a FIC course on deep learning principles and practical applications including CNNs, TensorFlow, PyTorch, and optimization techniques.

Completed a foundational FIC course on computer vision and machine learning covering OpenCV, feature extraction, classical ML models, and dataset preparation.

Completed coursework in naval engineering with studies in calculus, physics, and algorithms, and practical programming experience in C++.