Introduction
Mykola Senk learned to read logistics tables with one eye on the news and the other on a warehouse door that might not open tomorrow. Pallets of medicine, generators and blankets looked orderly only until the route changed at noon.
Mykola lives between Warsaw and Berlin and works on AI-supported logistics for uncertain conditions. His path into the field began with displacement, a damaged business and the need to move aid when information was incomplete.
Story of the Path into AI
During the first months of rebuilding supply routes, Mykola saw how chaotic data about stock, border delays and vehicle availability could affect people directly. Perfect planning was impossible; robust planning mattered more. He learned optimization, risk assessment and how to treat uncertain data without pretending it was clean.
His first system prioritized aid items by urgency, shelf life and transport windows. It worked until local contacts warned that one route was technically open but practically unreliable. The model did not know the driver who had crossed the area the night before.
Mykola added a human-network layer to the process. Data could suggest options; people with recent local knowledge had to challenge them.
Current Work
Today he advises aid organizations and small logistics firms. In one delivery of medical equipment, a model offered three routes. Mykola chose the slower one after checking with contacts who understood the situation on the ground. The result was not elegant, but it arrived.
He is careful about crisis technology. AI can help sort priorities and expose conflicts, but a misleading confidence score can be dangerous. In humanitarian logistics, uncertainty is not a technical embarrassment. It is part of the truth.
Personal Advice
“In a crisis, the best AI is not perfect; it is honest about uncertainty,” Mykola says. He advises teams to build systems that can be contradicted quickly by field knowledge.
Key Facts
Age and place: 44, Warsaw and Berlin.
Background: displacement, entrepreneurship, work under uncertainty.
Entry into AI: system prioritizing aid by urgency, shelf life and transport windows.
Focus today: humanitarian logistics.
Typical tools: optimization, risk models, supply-chain analysis.
Werkstattnotiz
Mykola keeps a route plan marked with three colours and one handwritten phone number. The phone number mattered more than the colours that day. He is now testing how planning tools can store such fragile knowledge without turning it into stale authority the next morning.