Remi Cadene

Remi Cadene is a French computer scientist and entrepreneur specialising in Artificial Intelligence, Deep Learning, Computer Vision, Natural Language Processing, and Autonomous Driving. He is currently the Co-Founder and CEO of UMA, a role he has held since October 2025 in Paris. Prior to this, he worked as a Principal Research Scientist at Hugging Face from March 2024 to December 2025. Between April 2021 and March 2024, he was a Staff Scientist at Tesla, contributing to AI and Autopilot development.

Remi’s academic career includes postdoctoral research positions at Brown University in the United States and at Sorbonne University in Paris from July 2020 to March 2021. He earned his PhD in Computer Science from Sorbonne University in July 2020, focusing on deep learning and computer vision. Before his PhD, he completed a Master’s degree in Computer Science at Pierre and Marie Curie University between 2014 and 2016, specialising in Big Data, Machine Learning, and Knowledge Representation. He also holds undergraduate degrees in Computer Science from Pierre and Marie Curie University and in Economics and Financial Management from Université Paris Cité and Paris-Sorbonne University Abu Dhabi.

Remi has gained practical experience through research internships at Facebook AI and Tesla, where he worked on vision and language projects, deep learning, and improvements to Tesla Autopilot. Earlier, he contributed to projects like VISIIR at Laboratoire d’Informatique de Paris 6, exploring semantic image annotation, and he worked as a freelance web developer for OpeningStage, building social network web applications.

He has received awards for his data science skills, including ranking 1st in the online round and 4th in the final of the Data Science Game organised by Microsoft, Axa, and Capgemini in 2016. His professional focus spans research, engineering, and applied AI solutions, combining academic expertise with industry experience in AI-driven technologies.

Remi Cadene was born in France. From an early stage, he showed interest in technology, computers, and mathematics, which later shaped his academic and professional career. He began his higher education in Economics and Financial Management, completing his first two years of undergraduate studies at Paris-Sorbonne University Abu Dhabi from 2012 to 2013.

He then continued his undergraduate studies at Université Paris Cité, where he completed Licence 3 in Economics and Financial Management in 2015. At the same time, he pursued a degree in Computer Science at Pierre and Marie Curie University from 2010 to 2014, gaining a strong foundation in programming, algorithms, and computational methods.

In 2014, Remi enrolled in a Master’s programme at Pierre and Marie Curie University, completing it in 2016 with a specialisation in Big Data, Machine Learning, and Knowledge Representation. During this period, he also began practical work, including internships and research projects. In 2015, he worked at Laboratoire d’Informatique de Paris 6 (LIP6) on image classification using deep learning. In 2016, he undertook another research internship at LIP6 focusing on deep learning, convolutional neural networks, and computer vision.

From 2014 to 2015, he also worked as a freelance web developer for OpeningStage, a startup supported by Crédit Agricole, developing social network web applications using CakePHP, MySQL, and JavaScript.

Remi began his PhD in Computer Science at Sorbonne University in October 2016 and completed it in July 2020. His research focused on deep learning, computer vision, and semantic understanding of images. During his PhD, he also worked as a teaching assistant. In 2018 and 2019, he completed research internships at Tesla, working on improving Autopilot using deep learning and weakly supervised learning, and at Facebook AI, contributing to vision and language projects under Devi Parikh.

After completing his PhD, he joined Sorbonne University and Brown University as a postdoctoral researcher from July 2020 to March 2021, where he continued his work in AI and deep learning. From April 2021 to March 2024, he worked as a Staff Scientist at Tesla, applying AI to autonomous driving systems. From March 2024 to December 2025, he served as Principal Research Scientist at Hugging Face, focusing on applied AI research.

In October 2025, Remi co-founded UMA in Paris and became its CEO. He currently leads the company, combining his academic knowledge and industrial experience to develop AI technologies. Over his career, he has contributed to multiple projects, publications, and AI applications, including VISIIR for semantic image annotation and improvements to Tesla Autopilot. He has received recognition for his work in data science, including top rankings in the Data Science Game organised by Microsoft, Axa, and Capgemini.

Today, Remi Cadene continues to lead UMA while actively contributing to AI research, engineering, and practical applications across autonomous driving, computer vision, and natural language processing.

Remi Cadene’s vision is to advance Artificial Intelligence in ways that make machines understand the world more like humans. He focuses on creating AI systems that can see, interpret, and learn from images, text, and other data. His work combines deep learning, computer vision, natural language processing, and autonomous driving to solve real-world problems. He aims to bridge the gap between research and practical applications, making AI more useful and safe for industries such as transportation, healthcare, and technology. His goal is to lead teams that develop innovative AI tools to improve daily life.

Remi Cadene has been recognised for his contributions to data science and AI research. In 2016, he ranked first in the online round of the Data Science Game organised by Microsoft, Axa, and Capgemini, and fourth in the final competition. His research work at Tesla, Hugging Face, and universities has been influential in deep learning, autonomous driving, and computer vision. He has contributed to projects like VISIIR, improving semantic image annotation, and enhancements to Tesla Autopilot. His achievements reflect his expertise in AI research and practical applications, earning him respect in both academic and industrial communities.