• Designed solutions involving Generative AI, Computer Vision and Natural Language Processing to effectively analyze and extract data from a major bank scanned documents.• Developed and refined prompt engineering techniques to optimize the Large Language Models extraction of key data fields, consistently achieving over 95% accuracy across the vast majority of fields.• Implemented machine learning classification models to effectively categorize documents or specific sections within them, involving extensive experimentation to optimize performance and accuracy.• Integrated the pipeline together,including parsing LLMs output, to ensure efficient and seamless processing.

• Developed a scalable marketing data lake to streamline data management and analytics.• Designed a robust data architecture, transitioning from legacy systems to cloud technologies.• Leveraged Amazon Web Services cloud components and Apache Spark to improve data processing efficiency, achieving significant reductions in both operational and storage costs.

• Implemented multimodal registration of satellite images using Convolutional Neural Networks (CNNs) to align data from different imaging modalities, resulting in the successful completion of my Master’s Thesis.• Conducted a comparative analysis between a feature-based registration algorithm and a deep learning-based unsupervised image registration framework, evaluating their accuracy, efficiency, and performance.

• Developed automation solutions for packaging processes, including robotic arm/manipulator simulations.• Optimized a palletizing cell, resulting in a significant reduction in the time required to palletize products.