Barrie Kersbergen

Barrie Kersbergen

Data Scientist & PhD candidate

University of Amsterdam


Barrie Kersbergen joined in 2010 as a data scientist. His main focus is solving business problems by improving processes with scalable recommendation systems. Examples of his work are the recommendation systems ‘others also viewed’, ‘often bought together’, ‘look further’, ‘visual recommendations’ and ‘search ranking’ functionality, that serve millions of items to millions of customers. In January 2021, he started as an external PhD candidate at the University of Amsterdam in the “AI for Retail Lab”.

Guest lectures

We will present our paper Serenade - Low-Latency Session-Based Recommendation in e-Commerce at Scale about a novel session-based recommendation system for ecommerce.