Patrick de Oude
Patrick de Oude is a Senior Data Scientist at Albert Heijn, a leading Dutch supermarket chain, where he focuses on operation data science projects with a specific emphasis on reducing food waste. He has a strong background in artificial intelligence and has used these skills to drive data-driven initiatives at Albert Heijn.
Patrick De Oude received his Master's degree from the University of Amsterdam in 2006 and his PhD in 2010. His academic background and industry experience has equipped him with a strong foundation in machine learning, with specific interest in causal inference, experimention, reinforcement learning, probabilistic modelling and inference, which he applies to real-world problems at Albert Heijn.
Patrick De Oude's work at Albert Heijn aligns with the company's broader sustainability strategy. Albert Heijn aims to eliminate at least half of the waste across the food chain by 2030. Patrick De Oude's work is a critical part of this effort, using data science and artificial intelligence to drive food waste reduction initiatives.
Sessions
This talk describes the development and deployment of a reinforcement model to reduce food waste in a supermarket chain. Markdowns are dynamically increased through the day on short shelf-life products following a particular policy. The goal is to minimize food waste without significantly increasing the cost of the markdowns. The sequence of choices of markdown levels is modelled as a Markov Decision Process and offline Q-learning is used on historic data to learn a policy. The talk introduces the context of the problem, how a reinforcement model was applied, and the challenges faced with offline and online evaluation.