Ignacio Botella is an Applied Scientist with 10 years of hands-on experience building and deploying AI systems across computer vision, NLP, time-series and tabular data. He has led end-to-end projects—from research and model design to production deployment—most recently developing a 3D CBCT dental imaging diagnostic tool and RAG systems with fine-tuned transformers. His background blends an MS in Artificial Intelligence from KU Leuven and an engineering foundation from Universidad Politécnica de Madrid, enabling rigorous modeling and practical engineering. At companies like Indra and dezzai he delivered segmentation, detection, tracking, and traffic forecasting pipelines, demonstrating both research depth and operational pragmatism. Now based in Dublin and working at DocuSign, he focuses on translating advanced deep learning methods into robust, deployable products. An understated strength is his ability to span modalities—vision and language—to build integrated solutions that solve real-world problems.
10 years of coding experience
5 years of employment as a software developer
Master of Science - MS Artificial intelligence, Master of Science - MS Artificial intelligence at KU Leuven
Master of Engineering - MEng Ingeniería de telecomunicaciones, Master of Engineering - MEng Ingeniería de telecomunicaciones at Universidad Politécnica de Madrid
This repository contains a python program that performs a genetic algorithm in which the chromosome has variable length. The algorithm receives a table in which each column represents an entity to be chosen (eg. an enterprise), and each row represents an item to be selected (eg. a product), with its corresponding weight. More info in the README file.
Contributions:76 commits, 4 PRs, 65 pushes in 2 years 5 months
Contributions:6 pushes, 1 branch in 2 years 10 months
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