Ruslan Voropai

Building ML and AI systems in a cross-functional Data Science team: ML & Data Engineering → Demand forecasting with ensemble/meta-models → MLOps library for model/data versioning and drift monitoring → Fault classification for trucks → Real-time anomaly detection on fiber-optic sensors Gen AI & NLP → LLM memory and RAG optimization for a custom chatbot product → RAG retrieval over scientific articles (graph + vector search) → Local vs cloud LLM evaluation for podcast analysis → Сopilot skills for data team

→ Developed computational methods for stochastic and data-driven optimization, including model predictive control of PDE systems under uncertainty → Implemented numerical solvers and simulation pipelines in Python for large-scale optimization problems → Published peer-reviewed research in Mathematics (MDPI) and Springer → Taught "Data-Driven Optimization for Machine Learning" and supervised student projects

Machine Learning, Numerische Optimierung, Datenanalyse,

Automatisierung, Diagnose, Vorhersage

Automatisierung, Mess-, Steuerungs- und Regelungstechnik, Energieanlagen