Yacine Khraimeche
About Yacine Khraimeche
Yacine Khraimeche is an Applied Scientist specializing in Computer Vision at Dialpad, where he has worked since 2021. He has a strong academic background in computer science and experience in developing computer vision algorithms, as well as expertise in deep learning techniques.
Work at Dialpad
Yacine Khraimeche currently holds the position of Applied Scientist specializing in Computer Vision at Dialpad. He has been with the company since 2021 and is based in Montreal, Quebec, Canada. In his role, he has contributed to the development of computer vision algorithms and participated in research projects that integrate computer vision with natural language processing. His work focuses on leveraging deep learning techniques to address various challenges within the field.
Education and Expertise
Yacine Khraimeche has an extensive educational background in computer science. He studied at Lycée Louis-le-Grand, where he completed a Classe préparatoire in Mathematics and Computer Science from 2012 to 2015. He then attended École Polytechnique, earning an Engineer's degree in Computer Science from 2015 to 2019. Following this, he pursued a Master of Science in Computer Science at Polytechnique Montréal from 2018 to 2020. His expertise lies in deep learning techniques specifically applied to computer vision challenges.
Background
Yacine Khraimeche has gained diverse experience in the tech industry. He began his career as a Software Engineer Intern at Mindsay in 2017, where he worked for two months in the Paris Area, France. In 2018, he served as a Research Intern at GoPro for four months in the Paris Area, France. He also worked as a Teaching Assistant at École Polytechnique de Montréal from 2019 to 2020, contributing to the academic environment in the Montreal, Canada Area.
Research Contributions
At Dialpad, Yacine Khraimeche has made significant contributions to research projects that focus on the intersection of computer vision and natural language processing. His work involves developing innovative algorithms that enhance the capabilities of computer vision systems. This research is essential for advancing the applications of computer vision in various domains, demonstrating his commitment to pushing the boundaries of technology.