People in DSML Kazakhstan

currently I work on low latency neuromorphic event based vision for robotics; Previously did autonomous drone swarms (pixhawk+jetson) for AgriTech and computer vision;

Yurt Tech is an innovative Kazakhstani IT company based in Astana, creating software at the intersection of national heritage and cutting-edge technologies. Key Focus Areas: Software Development: Creating high-quality software with a focus on testing, integration, and customized solutions. IT Outsourcing: Project management, technical support, IT consulting, and infrastructure management. Mission: The name "Yurt" (yurt) was chosen deliberately: it symbolizes comfort, security, and harmony, combining nomadic traditions with the modern digital world.

Software QA Engineer with 8+ years of experience testing web, desktop, API, and embedded automotive EV systems, combining manual and automation approaches to improve release quality and reduce production defects, along with a growing focus on using AI and Data to improve testing effectiveness. Experience spans REST microservices, trading platforms, banking, TV streaming, e‑commerce, and EV wall-box chargers in agile and hybrid (on-site, remote) environments. Quickly adapting to new tech stacks, owning automation frameworks, and collaborating closely with developers, testers, and product stakeholders. Using AI tools at a basic level to speed up test design, log analysis, and documentation, actively developing Data skills to move towards QA + Data hybrid roles.

Master’s student in AI at Bocconi University, building on a solid foundation with a BSc in AI from the University of Pavia/Milan. Deeply passionate about the practical applications of Deep Learning, GenAI, LLMs, and Autonomous Agents.

ML engineer and researcher with 2.5+ years of experience in computer vision and generative AI. I specialize in diffusion models (fine-tuning FLUX, ControlNet, LoRA), portrait animation pipelines, video generation, and the development of generative CV systems—from researching SOTA methods to production deployment.

My research interests lie from developing large multimodal models to practical computer vision tasks. Prior to that I focused on developing methods for image-to-image tasks such as super-resolution, image/video enhancement, and digital image processing part of which have been accepted to top-tier conferences and deployed in production environments serving millions of users.