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SYSE 580B3 - Network-Based Complex Systems Engineering

  • 3 credits
View available sections
Integrates network-based models and deep learning to solve complex systems engineering problems. Analyzes system architecture through graph metrics, motifs, and probabilistic models. Creates predictive frameworks using Artificial Neural Networks (ANN) and Graph Neural Networks (GNN) to support the design and analysis of large-scale complex systems.

Prerequisite

CS 345 (Machine Learning Foundations and Practice) or DSCI 369 (Linear Algebra for Data Science) or MATH 160 (Calculus for Physical Scientists I (GT-MA1)) or MATH 369 (Linear Algebra I) or STAT 301 (Introduction to Statistical Methods) or STAT 315 (Intro to Theory and Practice of Statistics); Senior Standing with minimum overall 3.0 GPA. Completion of AUCC Category 2 with a minimum B grade for undergraduate enrollees

Textbooks and Materials

Please check the CSU Bookstore for textbook information. Textbook listings are available at the CSU Bookstore about 3 weeks prior to the start of the term.

Instructors

Yinshuang Xiao

Yinshuang.Xiao@colostate.edu

Assistant Professor of Systems Engineering

Dr. Yinshuang Xiao conducts interdisciplinary research at the intersection of systems science, network science, and data-driven engineering design. Her work is centered on understanding and designing complex socio-technical systems, with a strong emphasis on human-AI collaboration, human-system integration, and engineering for dynamic, interconnected environments.

The applications of Dr. Xiao’s research span a wide range of domains, including transportation systems, product market systems, electric vehicle (EV) charging planning, urban infrastructure, energy systems, and smart manufacturing. Key research themes include: 1) local-level network-based bottom-up design of complex systems; 2) engineering and design of complex systems with temporal dynamics; 3) AI-integrated system design for adaptive and responsive solutions; 4) multidimensional network modeling across interdependent systems.