Yuwen Huang’s homepage

welcome! I am an information theorist in statistics, optimization, and combinatorics. I develop graphical-model and quantum-enabled methods—Bethe/graph-cover tools, tensor networks, distributed quantum systems—for provable, scalable inference and optimization, with applications in machine learning (ML).

Research interests

• Probabilistic graphical models & combinatorial inference for scalable learning and uncertainty quantification.
• Optimization for machine learning (ML) and decision-making (convex/nonconvex methods with provable guarantees).
• Tensor-network and quantum-enabled inference methods for high-dimensional data and ML model compression.
• Distributed quantum computing & quantum networks as emerging platforms for data-intensive analytics.

You can reach me at yuwen.huang@link.cuhk.edu.hk, or find more about my work on Google Scholar and ORCID.