Shujian Yu

Shujian Yu is an Associate Professor II (part-time) in Machine Learning at the Department of Physics and Technology, UiT The Arctic University of Norway, located in Tromso. He specializes in developing machine learning methodologies with applications spanning neuroscience, computer vision, and industrial processes.

Research Focus

His research integrates information theory with machine learning, focusing on:

• Novel divergence measures (Cauchy-Schwarz, Rényi entropy) for time-series analysis
• Interpretable neural networks for brain network-based psychiatric diagnosis
• Causal discovery methods for industrial fault detection
• Information bottleneck approaches for feature selection

Publication Trends

Recent works (2022-2025) demonstrate strong emphasis on information-theoretic learning, graph neural networks, and applications in neuroscience and computer vision. Publications appear in premier venues including IEEE Transactions, Neural Networks, and ICLR, with consistent focus on model interpretability and efficiency.

Research Group

Member of UiT's Machine Learning Group, collaborating with researchers in neuroscience, signal processing, and data science.