讲座内容：

     One of the challenges facing life cycle assessment (LCA) research and practice is missing data. Due to lack of primary data or high cost of collecting primary data, LCA studies often need to make unrealistic assumptions, leading to inaccurate results. To address this challenge, we have developed new computational approaches using data science techniques to estimate missing data in LCA solely relying on limited known data.
主讲人信息：

      Ming Xu is an Associate Professor and Director of China Programs in School for Environment and Sustainability and an Associate Professor in Department of Civil and Environmental Engineering at the University of Michigan, Ann Arbor. He earned his BS and MS from Tsinghua University, China, and PhD from Arizona State University, all in environmental engineering. His research focuses on environmental footprint and environmental impacts of emerging technologies.

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