DING Tianran

About

A researcher specializing in Life Cycle Assessment (LCA) with a years of track record in sustainability analysis, machine learning, and spatial modeling. With a Ph.D. in Environmental Science from Université libre de Bruxelles and over 10 years of international experience in academia and applied research, my work focuses on advancing LCA methods and applying them to emerging materials and technologies, especially for nanomaterials and bio-based systems. I am passionate about integrating data-driven approaches and environmental modeling to support sustainable decision-making across sectors.

Mission

At LIST, I contribute to multiple research projects, such as development of machine learning-based characterization factors for chemical toxicity assessment, nanomaterials, and ecosystem services for Life Cycle Assessment

Skills and expertise

  • Life Cycle Assessment (LCA): Territorial LCA, industrial applications, Brightway2, SimaPro
  • Machine Learning for Sustainability: Python (XGBoost, Gaussian Processes), data integration in LCA
  • Spatial Analysis & Modeling: QGIS, Google Earth Engine, GIS-integrated environmental models
  • ESG Analysis: ESG reporting, investment fund assessment, CFA-ESG certified

Latest Publications

Driving sustainability at early-stage innovation in production of zinc oxide nanoparticles

<p>Carreira-Barral I., Díez-Hernández J., Igos E., Saidani M., Ding T., Ramos da Silva T., Monteiro H., Stingl A., Farias P.M.A., Cardozo O., Ibáñez J., García-Moral A., Tamayo-Ramos J.A., Rumbo C., Barros R., Martel-Martín S.</p>

<p>Sustainable Production and Consumption, vol. 55, pp. 353-372, 2025</p>

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