Worked in ML at Lamoda, Mail.ru, and HeadHunter, and also taught at HSE and Bauman Moscow State Technical University. Was one of the creators of the ODS community. Currently develops the Yandex machine learning brand and helps organize conferences — such as HighLoad++, PyCon, DUMP, and Data Fest.

Worked as a Yandex DevRel manager for ML and mobile development. Built Yandex’s external ML specialist community from scratch and prepared over 100 Yandex speakers for conference presentations. Heads the program committee for Practical ML Conf, manages PR activities for Yandex Research, and the ML editorial team for the channels «Dushny NLP», «Recommendations», ML Underhood, CV Time, Speech Info. Has been producing international festivals and forums in Russia and CIS for 10 years. Passionate about AI and ML, and pets a toy poodle.

Has been working in machine learning since 2010. Defended his Candidate of Sciences dissertation in 2013, currently writing his doctoral dissertation on the application of multimodal architectures for tasks of passive multimedia content safety. Heads the FusionBrain multimodal generative AI laboratory at the AIRI Institute of Artificial Intelligence. One of the founders of the Kandinsky family of models, teaches at Samara University and ITMO, gives lectures, and writes about AI and ML events on the Telegram channel @complete_ai. Author of over 100 scientific publications, including in top-tier journals (Q1/Q2) and Core A/A* conference proceedings. H-index: 14.

Over 10 years in AI — has worked at Yandex, VK, and Huawei. Defended a dissertation on text analysis and is currently an associate professor at the Higher School of Digital Culture, ITMO. Author of the Telegram channel @valuableai.

Daniil Burlakov, Head of Recommender Products Sector Graduate of the Mechanics and Mathematics Faculty of Moscow State University and holds a Candidate of Sciences degree in Physics and Mathematics. Has been working at Yandex since 2016. Led the development of recommendations for Music, Kinopoisk, Afisha, and Bookmate.

Training Infrastructure Development Group Graduated from the Computational Mathematics and Cybernetics faculty of Moscow State University. Currently works on developing training infrastructure for DL models for recommender systems and their implementation in Advertising Technologies. Helps other teams utilize advertising developments in training recommender models.

Headed the development of computer vision products and algorithms at Yandex for 9 years. Currently responsible for the direction of experimental products and technologies based on artificial intelligence. Member of the expert council for the Yandex Science Prize.

Graduated from St. Petersburg State University and the Computer Science Center (St. Petersburg branch of Yandex School of Data Analysis). Worked on the CatBoost machine learning library, was the lead developer of the GPU version of the library. Has been working at Yandex since 2014, involved in developing technologies around machine learning and high-performance computing on GPUs. Heads the Machine Learning direction at Yandex Cloud. Additionally, he is the academic supervisor for the data analysis track of the «„Software Development and Data Science“» master’s program at the Faculty of Mathematics and Computer Science of St. Petersburg State University.

Heads the YandexGPT pretraining team — the family of large language models already used in most Yandex products. His team’s task is to create the smartest possible model capable of answering any user question with minimal fine-tuning.

Graduated from the Computational Mathematics and Cybernetics faculty of Moscow State University, worked at SberDevices where he was responsible for search quality. Currently develops Yandex’s recommender technologies. Enjoys track and field athletics, Formula 1, and game theory. Graduated from music school with a degree in violin.

Develops core image analysis technologies at Yandex. Interested in multimodal visual-text models. Defended his Candidate of Sciences dissertation in 2022, teaches at MIPT and Yandex School of Data Analysis. Enjoys tennis and trekking.

Heads the team working on computer vision technologies at Yandex. Current focus is the development of YandexVLM in areas where text or graphic elements in images are important. Enjoys fishing, football, and memes. Runs the Telegram channel @blog_toxa — about AI, management, and memes.

Expert in the field of machine learning with an applied focus, ten years of experience, and the title of Kaggle Grandmaster. Worked on anti-fraud tasks at Avito, built recommendations, and set up high-load ML infrastructure at Joom. Currently works on computer vision tasks. Outside of work, he loves sports data analysis, InfoSec, and electronic music. Has ridden a burning bus, organized ML training sessions, worked as a motion designer, and was a co-author of a course with 100,000+ students.

Completed his undergraduate, master’s, and postgraduate studies at MIPT (FPMI FIT), worked at ABBYY for 3 years, and at Yandex News and Search for 4.5 years. Won several ML contests from Telegram. Created the morphological analyzer rnnmorph, the poetry generator rupo, popular summarization models, and the Russian-tuned language model Saiga. Currently works as a Senior Machine Learning Engineer at Booking.com.

Founder of the Better Data Community. Creator of popular Russian LLMs and the VikhrModels benchmark, released as open source. Contributor to Kandinskiy1-2.2.

Pursuing a Ph.D. at the University of Glasgow, specializing in using transformer models for big data-based recommender systems. Writes articles for leading scientific journals and conferences on recommender systems RecSys, WSDM, and ACM TORS. His work was recognized as the best paper at RecSys 2023 and was a nominee at RecSys 2022. Has over 10 years of industry experience, held leadership positions at major tech companies (Amazon and Yandex), and was a co-founder of the startup E-Contenta, specializing in recommender systems. Administers the Telegram community #recommender_systems.

Heads the recommendations team at Avito. Kaggle Master and prize-winner in recommender system competitions. Teaches the ML System Design course at the Avito Analysts Academy.

Has been at Yandex for over 10 years: started as an intern, grew to head of the speech recognition service, managed the NLP department for the last two years, and became CTO of R&D a month ago. Taught algorithms and machine learning at School of Data Analysis. Lives and works in Minsk.

Over 10 years of experience in ML and AI. Worked at Samsung, Kaspersky, Huawei. Currently heads the YandexGPT Alignment team — the family of large language models used in most Yandex products.

Graduated from MIPT, worked as a researcher at the Interdepartmental Supercomputer Center of the Russian Academy of Sciences, developed face recognition technologies as a lead researcher and developer at NtechLab. His interests include deep learning, computer vision, and information retrieval. Planned to research computer networks, but ended up working with neural networks. Enjoys fishing and fashion videos.

8 years in science. Worked on high performance computing and wrote a dissertation on efficient computations in hydrodynamics. For 7 years, has been working on machine learning in various Yandex services (Search, Mail, Scoring, Speech Synthesis). Currently responsible for the video translation technology in the browser and speech synthesis for Alice and audiobooks.

Graduated from MIPT with a degree in «„Applied Mathematics and Physics,“» holds a bachelor’s degree in oceanology and a master’s degree in petroleum engineering. Worked at the Schlumberger research center. Joined Yandex in 2018 as an analyst in one of the fintech projects. After 2 years, joined the Alice and Smart Devices team, which shifted focus to noise and echo cancellation tasks in smart speakers. Within a year, managed to establish testing processes, create algorithms, and transition Yandex smart devices to in-house solutions. Nikita continued to develop his career in this direction and has held the position of Head of Voice Input Technology Service for over a year. Together with his team, he is responsible for developing voice input technologies across all Yandex products: Alice, Keyboard, Translator, Search, Browser, and others. While working on voice technologies, he found a solution to ensure the audibility of fundamentally new smart devices — for example, far-field TVs. Also significantly improved the quality of algorithm performance and created new features based on the service’s technologies.

Received a bachelor’s degree from the Department of Mathematical Forecasting Methods, Computational Mathematics and Cybernetics faculty, Moscow State University. Joined Yandex in 2020 to develop neural network recommender technologies. From 2022 to 2025, led the team responsible for R&D for recommender technologies across the entire Yandex ecosystem. Participated in projects to improve recommendations for Music, Market, Kinopoisk, Alice, Lavka, Search, and Advertising. Runs the Telegram channel about recommender systems @inforetriever.

Researches and develops machine learning-based solutions to combat hackers and find vulnerabilities in services that use ML. Previously responsible for the ML direction at Positive Technologies. Currently helps the Yandex Go team scale security in popular services. Believes that technology can make information security stop being a headache.

Received a PhD in Computer Vision from Skoltech. Worked as a researcher at Yandex and Samsung Research. Founded the startup Avaturn, which uses 3D scanning and human modeling technology.

Graduated from HSE and Skoltech. At Yandex, he teaches LLMs to reason. Before Yandex, he worked on development and research of generative methods applied to speech technologies at MTS AI. Worked at Samsung and Huawei research centers. Has published scientific papers at ICLR, ICML, NeurIPS, ICASSP, Interspeech conferences. Teaches at HSE.

Graduated from the Computational Mathematics and Cybernetics faculty of Moscow State University and the University of Toronto. Has been working with ML and ML systems for 11 years: developing his own startup, conducting academic research, and solving applied problems in industrial projects. At Yandex, he is responsible for the overall ML infrastructure. Interested in ML for Systems, RL, and Causal Discovery.

Graduate of the Computational Mathematics and Cybernetics faculty of Moscow State University and Yandex School of Data Analysis. Has been at Yandex since 2015. Works on projects related to computer vision: improving image search, recognizing road signs for Yandex Navigator, improving autonomous driving technology, developing video duplicate search technology. Currently responsible for software development for a new warehouse robot at Yandex Robotics. Also organizes training courses and lectures at Yandex School of Data Analysis on courses about self-driving cars, deep computer vision, and graphics.