çağlayan Tuna
About çağlayan Tuna
Çağlayan Tuna is a Machine Learning Engineer currently working at Inria in Paris, France. He has a background in telecommunications and has contributed to the Tensorly library while collaborating on AI projects in the aerospace industry.
Work at Inria
Currently, Tuna works as a Machine Learning Engineer at Inria, starting in 2022. His role is based in Paris, Île-de-France, France, and involves on-site collaboration. Prior to this position, he worked at Inria from 2020 to 2022 in Rennes, Brittany, France, where he held a hybrid work arrangement. During his tenure at Inria, Tuna has contributed to various projects, including a collaborative initiative with Airbus Helicopters aimed at improving quality control processes in the aerospace sector through artificial intelligence.
Education and Expertise
Tuna has a solid educational background in telecommunications and remote sensing. He earned a Master's degree in Satellite Communication and Remote Sensing from Istanbul Technical University, where he studied from 2015 to 2017. He also completed his Doctor of Philosophy (PhD) at the University of South Brittany from 2017 to 2020. His undergraduate studies in Telecommunication Engineering were also at Istanbul Technical University, spanning from 2009 to 2015. This academic foundation supports his expertise in machine learning and its applications.
Background
Tuna's educational journey began at Kabataş Erkek Lisesi, where he studied from 2005 to 2009. Following high school, he pursued a degree in Telecommunication Engineering at Istanbul Technical University, which laid the groundwork for his advanced studies. His professional experience includes an internship at Digiturk as a LigTv Transmission Intern in 2015, where he gained practical insights into the telecommunications industry. This diverse background has shaped his career trajectory in machine learning and engineering.
Contributions to Machine Learning
Tuna has made contributions to the Tensorly library, which focuses on tensor decompositions. This work is significant in the field of machine learning, particularly in the context of multi-dimensional data analysis. His involvement in such projects reflects his commitment to advancing the capabilities of machine learning tools and methodologies.