Hoda Eldardiry's research spans machine learning, knowledge discovery, and data mining -- with a focus on social network analysis, ensemble classification, and statistical relational learning. She is currently working on fraud analysis and anomaly detection, which has both government and commercial application.
Hoda is particularly interested in the relational characteristics of data, including recovering and utilizing hidden structures. She has developed algorithms that combine relational knowledge from multiple sources and propagate inference information across various relational models.
Dr. Eldardiry earned her Ph.D. and M.S. in Computer Science from Purdue University, and her Bachelor's degree in Computer and Systems Engineering from Alexandria University in Egypt.
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Fraud Detection for Healthcare
11 August 2013
Multi-domain Information Fusion for Insider Threat Detection
24 May 2013 | San Francisco, CA
An Analysis of How Ensembles of Collective Classifiers Improve Predictions in Graphs
29 October 2012 | Maui, HI