Hanzhang Wang is an applied researcher at eBay. He leads a team of developers and researchers working on AIOps and AI4SE solutions. His recent research interests include intelligent observability, AIOps, RCA, SE, ML and graph algorithms. He has multiple publications in top venues, including FSE, ASE, VLDB, TSC and CIKM. The research outcomes have been transferred into multiple production products for anomaly detection, root cause analysis, developer velocity, etc. Hanzhang also serves as the company-wide university partnership program manager. He received his PhD in Computing Science from the University of Michigan and joined eBay in 2018.


Technologies are disclosed herein for enhancing machine learning (?ML?) -based anomaly detection systems using knowledge graphs. The disclosed technologies generate a connected graph that defines a topology of infrastructure components along with associated alarms generated by a ML component. The ML component generates the alarms by applying ML techniques to real-time data metrics generated by the infrastructure components. Scores are computed for the infrastructure components based upon the connected graph. A root cause of an anomaly affecting infrastructure components can then be identified based upon the scores, and remedial action can be taken to address the root cause of the anomaly. A user interface is also provided for visualizing aspects of the connected graph.

Country: United States
Grant Date: December 20, 2022
INVENTORS: Phuong Nguyen, Hanzhang Wang
Hanzhang Wang - Applied Researcher

Hanzhang Wang