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.
- High-Performance Systems