Similarity-based link prediction for estimating life cycle inventory data

Ping Hou

University of Michigan

I am in a joint Ph.D. program in Resource Policy & Behavior at School of Natural Resource & Environment and Scientific Computing at Michigan Institute for Computational Discovery & Engineering. In my doctoral research, I explore computational approaches to addressing sustainability issues. In particular, I investigate approaches that would reduce data collection demands and leverage existing data to hasten policy development. My current research is centered on reducing data demands to increase the feasibility of Life Cycle Assessment (LCA). On the conference, I am going to present the similarity-based link prediction for estimating life cycle inventory data.


Life cycle assessment (LCA) measures the environmental impacts of a product in its whole life cycle from resource extraction through disposal. A good LCA study relies on the availability and quality of life cycle inventory... [ view full abstract ]


  1. Ping Hou (University of Michigan)
  2. Jiarui Cai (University of Michigan)
  3. Ming Xu (University of Michigan)

Topic Areas

• Life cycle sustainability assessment , • Network theory for industrial ecology


MS-13 » LCA new developments 2 (14:00 - Monday, 26th June, Room D)

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