Summary
Hanna Paulava is a Machine Learning Engineer with 11 years of experience bridging mathematical research and practical AI solutions, currently focused on energy flow forecasting at Exnaton and independent ML consultancy. She has spent the last five years specialising in deep learning and computer vision—building production-ready systems for manufacturing image analysis, temporal visual change detection, and video generation—while also tackling large-scale tabular problems and time series analysis. Her background in academic time-series research gives her an edge in principled model design and a bias toward interpretable, simple models when they suffice. She has led ML pipelines end-to-end, from data collection and augmentation to deployment and business-facing statistical engines, and is experienced with MLOps on GCP/AWS. Notably, she combines startup agility (building “AI presenter” engines and ML products) with enterprise-grade analytics and a habit of turning raw ML outputs into actionable business insights.
11 years of coding experience
9 years of employment as a software developer
Master of Computer Applications (M.C.A.), Applied Computer Data Analysis, 9.33, Master of Computer Applications (M.C.A.), Applied Computer Data Analysis, 9.33 at Belarusian State University
English, Беларуская, Polish, Русский