Tomer Fishman is an industrial ecologist whose research is focused towards understanding the materials that accumulate in our buildings, vehicles, infrastructure, consumer products, and green technologies, and how they form the interlinkages between well-being and welfare, economic development, and the environment. His work combines multiple approaches, including material stock and flow analysis, geographic information systems (GIS) and remote sensing, econometrics, and dynamic models.
Tomer Fishman is Assistant Professor of Industrial Ecology at the institute of Environmental Sciences (CML) at Leiden University. He has several roles in the International Society for Industrial Ecology, including co-chair of the conferences committee and board member of the socioeconomic metabolism section. Prior to joining the CML, he was a lecturer at the school of Sustainability, Reichman University Interdisciplinary Center (IDC) Herzliya, Israel.
He was at Yale University’s School of the Environment as postdoctoral associate at the Center for Industrial Ecology, where he conducted research on vehicles and wind turbines to assess the demand and supply of critical materials for green technologies, as part of the U.S. Department of Energy’s Critical Materials Institute.
Tomer obtained his Ph.D. in Environmental Studies and his Master of Engineering degrees from Nagoya University, Japan, on the subject of the accumulation of construction material stocks and its future trends and drivers. He has a B.A. in economics and East Asian Studies from the Hebrew University of Jerusalem, Israel.
Check out Tomer’s work here.
• Country- and global-scale drivers and forecasts of material stock & flow processes with dynamic models
• Mapping the materials stocked in buildings & infrastructure using geospatial (GIS) analysis and remote sensing
• Scenarios of demand and supply of critical materials in emerging “green” technologies
• Resource efficiency and circular economy
• Material stock & flow accounting and analysis
• Socio-economic metabolism
• Statistical, econometric, and data-driven analysis and forecasting