Mert has successfully defended his PhD dissertation on June 7th, 2023. The title of his dissertation is ‚ÄúTransparent Representation Learning for Graphs and Human-AI Collaboration‚ÄĚ. The committee members are Prof. Ambuj Singh, Prof. Francesco Bullo, Prof. Xifeng Yan. You can find the abstract of the dissertation below, and full dissertation from here.

Abstract: Graph data show relationships between entities in a variety of domains including but not limited to communication, social, and interaction networks. Representation learning makes graph data easier to use for graph tasks such as graph classification, link prediction, and clustering. The decisions on graphs depend on complex patterns combining rich structural and attribute data. Therefore, explaining these decisions made by representation learning models for high-stakes applications (eg, anomaly detection and drug discovery) is critical for increasing transparency and guiding improvements. Moreover, human expertise can guide machine learning decisions, raising questions about the interactions between humans and artificial intelligence that require further analysis.