Adriano Passos
About Adriano Passos
Adriano Passos is a Deep Learning Engineer with extensive academic and professional experience in mechanical engineering and data science. He currently works at Overview, focusing on anomaly detection models and AI transparency, and has previously held positions at various educational institutions and companies.
Current Employment Overview
Adriano Passos currently serves as an Engenheiro de Deep Learning at Overview, a position he has held since 2022. He works remotely and focuses on developing advanced models for anomaly detection in deep learning. His role involves applying robust optimization techniques and conducting research on model explainability to improve transparency in AI systems.
Previous Academic Positions
Adriano Passos has held academic positions as a Professor of Mechanical Engineering at two institutions. He worked at the Federal University of Technology - Parana from 2014 to 2015, and later at Grupo Educacional Opet from 2018 to 2019. In these roles, he contributed to the education of engineering students, sharing his expertise in mechanical engineering.
Research Experience
Adriano Passos has research experience as a Postdoctoral Researcher at Vale from 2020 to 2021. His research focuses on deep learning applications, particularly in the areas of Natural Language Processing and Computer Vision. He also emphasizes the importance of model explainability in AI systems, aiming to enhance their transparency.
Educational Background
Adriano Passos has an extensive educational background in engineering. He earned a Bachelor of Engineering in Mechanical Engineering from the Federal University of Technology - Parana, completing his studies from 2009 to 2014. He continued his education at the same institution, obtaining a Master of Science in Mechanical Engineering from 2014 to 2016, followed by a Doctor of Philosophy in the same field from 2016 to 2020. Additionally, he studied Data Science at Let's Code from 2021 to 2022.
Professional Achievements
Adriano Passos has achieved Kaggle Master status, indicating his proficiency in data science competitions. His expertise extends to developing state-of-the-art models in deep learning, with a focus on robust optimization techniques. He also specializes in the fields of Natural Language Processing and Computer Vision.