(734) 763-8644

Complex Systems, Engineering, Environmental and Climate Research, Physical Science
Data Mining, Data Visualization, Graph-Based Methods, Networks, Optimization, Statistics
Relevant Projects:



Chinese Society for Industrial Ecology
American Association for the Advancement of Science (AAAS)
American Society of Civil Engineers (ASCE)
Association of Environmental Engineering and Science Professors (AEESP)
International Input-Output Association (IIOA)
International Society for Industrial Ecology (ISIE)

Ming Xu

Associate Professor

School for Environment and Sustainability
Civil and Environmental Engineering, College of Engineering

Associate Professor of Civil and Environmental Engineering, College of Engineering

My research focuses on developing and applying computational and data-enabled methodology in the broader area of sustainability. Main thrusts are as follows:

  1. Human mobility dynamics. I am interested in mining large-scale real-world travel trajectory data to understand human mobility dynamics. This involves the processing and analyzing travel trajectory data, characterizing individual mobility patterns, and evaluating environmental impacts of transportation systems/technologies (e.g., electric vehicles, ride-sharing) based on individual mobility dynamics.
  2. Global supply chains. Increasingly intensified international trade has created a connected global supply chain network. I am interested in understanding the structure of the global supply chain network and economic/environmental performance of nations.
  3. Networked infrastructure systems. Many infrastructure systems (e.g., power grid, water supply infrastructure) are networked systems. I am interested in understanding the basic structural features of these systems and how they relate to the system-level properties (e.g., stability, resilience, sustainability).

A network visualization (force-directed graph) of the 2012 US economy using the industry-by-industry Input-Output Table (15 sectors) provided by BEA contains 405 industries. Each node represents a sector. The size of the node represents the economic output of the sector. The size and darkness of links represent the value of exchanges of goods/services between sectors. An interactive version and other data visualizations are available at http://mingxugroup.org/