Machine Learning Assisted Industrial Symbiosis: Using Neural Networks and Big Data to Identify Valuable Material Substitutions

Christopher Davis

university of groningen

Dr. Chris Davis is an Assistant Professor of Energy Informatics and Modeling at the University of Groningen. His research focuses on exploring how approaches such as Data Science, Big Data, Machine Learning, and Agent Based Modeling can be applied to enhance the study of energy and industrial systems.


A challenge of Industrial Symbiosis and waste valorization involves identifying novel uses of waste streams which can satisfy the demand for feedstocks needed by other industries. For these efforts, a variety of... [ view full abstract ]


  1. Christopher Davis (university of groningen)
  2. Graham Aid (Ragn-Sells AB)

Topic Areas

• Industrial symbiosis and eco-industrial development , • Open source data, big data, data mining and industrial ecology , • Circular economy


WS-10 » Understanding Industrial symbiosis (11:30 - Wednesday, 28th June, Room G)

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