In the first UNFOLD of Easter Term, Ramit Debnath discusses how imbalances in global knowledge production in energy research can be modelled
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In energy research, it is often observed that international policy lessons do not travel effectively across regions. There is a gap in understanding how knowledge is produced across geographies and whether there are embedded biases due to the source of funding, research team’s location or country of origin of the first author of the published work. Limited studies show that such biases can be due to a strong western influence on knowledge production and recommendations, linking high-income countries’ dominance over low-income countries’ policy decisions. Decolonising such biases are essential to designing effective policies that can support the developmental goals of low-and-middle-income nations. This talk discusses the decolonisation of energy research, which is a core field in architectural studies, explaining how network science and regression analysis are used to evaluate biases in knowledge production in the energy policy research domain.
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Dr Ramit Debnath is a Sustainability Fellow (Churchill College) at the University of Cambridge and a Visiting Faculty Associate in Computational Social Science at Caltech. He is also a research associate at the Centre for Natural Materials Innovation (Architecture), Energy Policy Research Group (Judge Business School) and Bennett Institute of Public Policy (POLIS). His research is at the intersection of data science, public policy and environmental design for energy and climate justice, specifically asking questions about how to place people at the heart of the net-zero transition. His work informs policy institutions, including the International Energy Agency, UK Government’s BEIS, UNDP, the Indian Government’s NITI Aayog and UN COP-26. He has a background in electrical engineering and sustainability sciences (Cambridge Engineering) and a PhD from Cambridge Architecture as a Gates Scholar.
Visit: https://www.ramitdebnath.org