معرفی
Amy Deng is an Assistant Professor at the Department of Mathematics and Computer Science, Eindhoven University of Technology (TU/e). Her research focuses on machine learning and data mining applications in social sciences and e-commerce, emphasizing explainable and robust AI techniques for temporal data analysis. She leads the Data Mining research group, contributing to advancements in graph neural networks, domain generalization, and societal event forecasting.
Her work integrates causal reasoning, spatiotemporal modeling, and graph-based approaches to address challenges in event prediction and dynamic knowledge representation. Recent projects include developing adaptive normalization techniques for non-stationary time series and contrastive learning methods for graph homophily analysis.
- Research Interests: Machine Learning, Data Mining, Explainable AI, Temporal Data Analysis, Social Event Forecasting
- Labs/Teams: Data Mining Group at TU/e
- Education: Not explicitly listed in available texts, but affiliated with TU/e's academic programs in computer science and data science.
Publications highlight contributions to graph neural networks (e.g., SimGCL), causal event modeling, and robust forecasting frameworks. She currently teaches courses on Generative AI Models, aligning with her research in advanced AI techniques.
