Dr Ramit Debnath

University Assistant Professor

Contact information

Trumpington Street
James Dyson Building
University of Cambridge
Cambridge
Cb21px
United Kingdom

Biography

Dr Ramit Debnath is a university assistant professor and an academic director at the University of Cambridge; leading the Cambridge Collective Intelligence & Design Group (camcid.github.io). He is a fellow of Churchill College and Cambridge Zero and has visiting academic roles at Caltech and Florence School of Regulation Global. Ramit sits on the steering committee of Cambridge's Centre for Human-Inspired AI (CHIA).

With a background in electrical engineering and computational social sciences, Ramit designs collective intelligence approaches to provide a data-driven, complex system-level understanding of barriers to climate action in the Anthropocene, their interactions, and how these translate to leverage points for policy and behavioural interventions at scale.

Previously, Dr Debnath has held positions at Caltech, Cambridge Computer Laboratory, UN Environment Program, International Energy Agency, Stanford University and IIT Bombay. Ramit had received his MPhil and PhD from the University of Cambridge as a Gates Scholar.

Ramit is a Fellow of the Royal Statistical Society and a Professional Member of ACM.

Research interests

I am interested in drawing policy and behavioural inferences using computational social sciences for application in climate mitigation and adaptation design. I view Responsible AI as a system design challenge and is interested in its broader alignment question with climate justice and sustainability. I also use big data from social media platforms to study information feedback loops that can affect social tipping points.

Keywords

Artificial intelligence, Complex systems, Data governance, Data science, Ethics, Machine learning, Policy, Social media, Social science

Publications

Updated publication list: https://camcid.github.io/publications.html

Selected publications:
1. Debnath, R., Ebanks, D., Roulet, T., Mohaddes, K. and Alvarez, R.M. (2023). Do fossil fuel firms reframe online climate and sustainability communication? A data-driven analysis, npj Climate Action, Nature Portfolio https://doi.org/10.1038/s44168-023-00086-x
2. Müller-Hansen, F., Repke, T., Baum, C.M., Brutschin, E., Callaghan, M.W., Debnath, R., Lamb, W.L., Low, S., Lück, S., Roberts, C., Sovacool, B.K., Minx, J.C. (2023). Attention, sentiments and emotions towards emerging climate technologies on Twitter, Global Environmental Change, Elsevier https://doi.org/10.1016/j.gloenvcha.2023.102765
3. Bardhan, R., Debnath, R., and Mukherjee, B. (2023). Factor in gender to beat the heat in impoverished settlements, Nature, https://doi.org/10.1038/d41586-023-02632-3
4. Debnath, R., Creutzig, F., Sovacool, B.K., and Shuckburgh, E. (2023). Harnessing human and machine intelligence for planetary scale climate action, npj Climate Action, Nature portfolio, https://doi.org/10.1038/s44168-023-00056-3
5. Debnath, R., Bardhan, R., and Bell, M. (2023). Lethal heatwaves are challenging India's sustainable development. PLOS Climate, https://doi.org/10.1371/journal.pclm.0000156. (Altmetric = 918)
6. Debnath, R., Reiner, D. M., Sovacool, B. K., Müller-Hansen, F., Repke, T., Alvarez, R. M., and Fitzgerald, S. D. (2023). Conspiracy spillovers and geoengineering. iScience, Cell Press, https://doi.org/10.1016/j.isci.2023.106166
7. Debnath, R., van der Linden, S., Sovacool, BK, and Alvarez, RM (2023). Facilitating system-level behavioral climate action using computational social science. Nature Human Behaviour, https://doi.org/10.1038/s41562-023-01527-7
8. Debnath, R., Bardhan, R., Shah, D.U., Mohaddes, K., Ramage, M.H., Alvarez, RM., and Sovacool, B.K. (2022) Social media enables people-centric climate action in the hard-to-decarbonise building sector. Scientific Reports, Nature Portfolio, https://www.nature.com/articles/s41598-022-23624-9

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The Cambridge Centre for Data-Driven Discovery (C2D3) brings together researchers and expertise from across the academic departments and industry to drive research into the analysis, understanding and use of data science and AI. C2D3 is an Interdisciplinary Research Centre at the University of Cambridge.

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