Machine learning and data systems for chemical engineering, industrial processes and document intelligence.
Email | Telegram | GitHub | GitLab | Saint Petersburg
I work at the intersection of chemical engineering, industrial data analysis and machine learning. My projects focus on practical ML systems: forecasting process parameters, analyzing industrial datasets, building OCR/LLM pipelines and turning research ideas into usable prototypes.
I am especially interested in applied AI for chemical production, oil and gas, process monitoring and engineering decision support.
| Project | Area | What it does |
|---|---|---|
| NeftecodeTeamRocket | Industrial ML | Predicts oxidative test results for multi-component oil formulations. Neftecode 2026 winner project. |
| SuccessfulBPMN | OCR / LLM / System Design | Asynchronous ML service for scanning and generating BPMN diagrams with detection, OCR and LLM-based structure recovery. |
| CoalGuard | Time Series / Monitoring | Demo platform for coal pile monitoring and 3-day fire risk forecasting. |
| DistillationColumnTemperaturePrediction | Chemical Process ML | Forecasts distillation column top temperature using weather data and regression models. |
| SteinerRL | Reinforcement Learning | Grid-based Steiner tree pipeline for pipeline network design experiments. |
| CorrProgram | Data Analysis Tooling | App for correlation analysis from CSV/Excel data with visualization and export. |
- Winner of Neftecode 2026 with an ML solution for oil formulation analysis.
- Prize winner at ITMO MegaSchool, ML System Design track.
- Prize winner of a Gazprom Neft olympiad with a full-stack ML concept for distillation column monitoring.
- Speaker and author on ML applications in chemical technology and industrial process forecasting.
Python | pandas | scikit-learn | PyTorch | time series | computer vision | OCR | LLM pipelines | FastAPI | Streamlit | Docker | JavaScript
I am building stronger end-to-end ML systems for industrial use cases: from data preparation and model training to backend services, interfaces, deployment and clear project documentation.