Shujian Yu

Shujian Yu is an Assistant Professor at the Department of Artificial Intelligence, part of the Faculty of Science at Vrije Universiteit Amsterdam. He is also affiliated with the Network Institute. His research focuses on Information Theory, Machine Learning, and Deep Neural Networks, with applications in causal discovery, brain network analysis, and generalization bounds.

Key research interests include:

• Information-Theoretic Methods for ML interpretability and robustness
• Transfer entropy and causal inference in complex systems
• Feature selection and dimensionality reduction techniques
• Brain network-based psychiatric diagnosis (e.g., schizophrenia analysis)

He teaches courses on Data Mining Techniques, Deep Learning, and Introduction to Reinforcement Learning. Recent work explores hierarchical state space models, Cauchy-Schwarz divergence applications, and Granger causality in chemical processes. His collaborations span interdisciplinary fields including neuroscience and industrial engineering.

Publications emphasize theoretical foundations while addressing practical challenges in ML generalization, adversarial robustness, and sequential decision-making.