Five university students are headed to eBay for summer internships this year after claiming top prize at the 2023 eBay University Machine Learning Challenge. The annual competition asks students to dream up innovative solutions to real-world ecommerce problems, rewarding top teams with valuable work experience while recruiting promising new talent to the company.
This year’s winning team, named NullPointer, included five graduate students from different universities across the U.S.:
Ao Shen, University of Chicago Urbana-Champaign
Yao Zhang, University of Washington
Meijin Li, Stanford University
Ye Yuan, Carnegie Mellon University
Yixiao Yuan, Columbia University
Together the team built a model that can accurately identify, extract, and label “named entities” – words or phrases that refer to specific people, places, brands, sizes, and so on – using a machine learning process known as Named Entity Recognition (NER). At eBay, NER is commonly used to automatically extract key information from listings and search queries. NullPointer and other competing teams worked with a dataset of 10 million item titles from eBay Germany’s sneaker category.
In all, 1,439 students from 206 universities formed 887 teams to enter the eBay University Machine Learning Challenge this year – the event’s biggest turnout yet.
Interested in joining the next competition? You can register late this spring via EvalAI.
