I’m a Machine Learning Software Engineer @ EPAM Systems. I have 7+ years of experience in developing software of various kinds - mostly, machine learning solutions. Currently I’m working on graph optimization and analysis for warehouses. Previously, I served as a Data Scientist / Machine Learning Engineer @ Alif 🇺🇿 building AI assistants for the automation of conversational experiences of our clients. I was also a Research Engineer @ Romanovsky Institue of Mathematics working on adapting machine learning methods including foundation models (see, e.g., smiles-gpt) and graph neural networks to chemistry. I received my Bachelor’s in Applied Mathematics & Computer Science from Lomonosov Moscow State University in Tashkent.

I’m mostly interested in deep learning and its applications in natural language processing, esp. the parts that make high-throughput, research-intensive solutions largely available in industry. But my interests are not strictly limited, and some of the projects I enjoyed being involved in (albeit shortly) are transaction fraud monitoring and credit scoring.

I try to be active on social media incl. Medium, Kaggle, and Github by sharing my thoughts and experiences on the field. Check out the references & pages on this website and feel free to reach out by any means that suits you best.

Recent News

• 2025/08/13-15. Mentored the runner-up and multiple other teams @ IT Park AI Hackathon!
• 2025/05/01. Started my new journey as a Data Sci / ML Eng @ EPAM!
• 2024/11/08. Finally retook the TOEFL and scored 108, marking a huge improvement from my previous 95 in October 2021!
• 2024/10/26-27. Mentored @ Women Techmakers Tashkent. See my Smooth & Fresh Introduction to Tabular Competitions (w/ scikit-learn, skrub, mlxtend, and feature-engine).
• 2024/10/12. 🎉 scikit-fallback v0.1.1.post0 is out! See also the documentation and the v0.1.0 release w/ bugfixes and new features such as anomaly-based fallback classification.