Nikita Vasiliev

Nikita Vasiliev is a mathematician and machine learning practitioner with a background in the Faculty of Mechanics and Mathematics at Lomonosov Moscow State University. His work sits at the intersection of low-level computer architecture and applied machine learning. With more than seven years of experience in ML, he has designed computers from the ground up, developed low-level hardware schemes for neural network architectures, and teaches a course on building a computer from scratch at Central University.

Nikita has worked as a machine learning engineer in large-scale industry. At VK, he built a recommendation engine for a media platform from the ground up, redesigning both the system architecture and core algorithms while migrating legacy code to a modern, production-ready stack. He later worked in applied research, focusing on translating machine learning ideas into real-world systems.

With over eight years of teaching experience, Nikita currently leads the undergraduate Data Science programme at Central University, combining academic leadership with hands-on teaching in AI and computer architecture. His teaching philosophy focuses on clarity, intellectual honesty, and engagement: he aims to make complex technical ideas accessible without oversimplification, using practical examples, thoughtful explanations, and carefully designed educational materials.