Elizabeth Haubert

Data Architect and Relevance Engineer

As a relevancy engineer and data architect, Elizabeth can engineer a solution to your data goals. With twelve years experience in high-performance systems, she has worked with a spectrum of data transformation needs from high-rate, high-precision time-series sensor data to terabyte-scale text and image retrieval systems for the US Patent and Trademark Office.

At a semantic level, she has worked at person identification and classification systems both in public and private-facing systems. Her work with Duke Health system helped patients better locate doctors by name, location and treatment programs. She has worked with Retail Relay to prototype internal-facing customer identification for retail fraud prevention.

When you ask Google What is learning to rank?, Liz has the first blog post to come up!

Lizā€™s Master thesis was in early work with image-based recommender systems.

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