Elastic Security: Susan Chang applies econometrics to anomaly detection

AI Impact Summary

Susan Chang’s background in econometrics provides a crucial foundation for her work building machine learning systems for Elastic Security. Her approach leverages statistical modeling and pattern recognition – core concepts from econometrics – to analyze high-volume security data and detect anomalous behavior. This approach is particularly relevant for handling time-series data, where identifying meaningful patterns over time is challenging, and relies heavily on machine learning models to identify behaviors.