Yandex Research is a team of scientists focusing on fundamental problems in machine learning.
What we do
We study computer vision and self-driving cars, natural language processing and speech technologies, search and recommendation systems. Our research helps to improve the technologies in Yandex products. We also publish our findings at leading machine learning conferences and contribute to the community by organizing competitions, workshops and tutorials.
How we support the community
A creative and collaborative scientific environment is essential for productive research in most fields. We strive to develop the Russian academic community through collaboration with students and universities. For instance, we launched a machine learning residency program to provide an opportunity to grow for early-career researchers. Also, in collaboration with scientists from world-leading universities, we organize projects that move machine learning forward.
Computer visionYandex Research team regularly contributes to the computer vision research community, mostly in the field of image retrieval and generative modelling.32 publications2 posts1 dataset
Natural language processingLanguage is one of the key forms of communication. We study methods of language representation and understanding to simplify human-computer interactions.21 publication1 post2 datasets
Large-scale machine learningToday, training most powerful models often takes significant resources. Our research aims to make large-scale training more efficient and accessible to the entire machine learning community.6 publications
Machine learning theoryWe study various aspects related to theoretical understanding of ML models and algorithms.24 publications2 posts
Graph machine learningGraphs are a natural way to represent data from various domains such as social networks, molecules, text, code, etc. We develop and analyze algorithms for graph-structured data.11 publications2 posts1 dataset
Probabilistic machine learningProbabilistic machine learning describes methods which enable reasoning and inference over unknown quantities. Commonly used in generative modelling, regression and uncertainty quantification.6 publications
Work with us
Join our research team and get an opportunity to engage in world-class applied and theoretical research, gain experience working on high-impact projects and publish at top-tier academic conferences. You will contribute to high-tech services like computer vision technologies, dialogue systems, neural machine translation and self-driving cars.