University Assistant Professor of Mathematics and Social Design
Teaching lead: Mathematics and Programming (Design Tripos)
Director, MPhil in Architecture and Urban Studies
Biography
Dr Ramit Debnath is a University Assistant Professor and Deputy Director of the Centre for Human-Inspired AI (CHIA). Ramit is an elected member of the Methods Advisory Group (MAG), Department of Work and Pension, UK Government. He leads the Cambridge Collective Intelligence and Design Group and climatRACES Lab, and has a visiting academic role at Caltech, where he co-leads the Climate and Social Intelligence Lab. He is the Maths and Programming teaching lead for the DesignTripos course.
Dr Debnath's research advances computational social science methodologies for climate and environmental sustainability. He actively builds interdisciplinary collaborations to tackle hard questions associated with the appropriate design of responsible AI systems for global good while delivering direct policy impact. For further information, visit his research group: https://www.collectivedesign.group.cam.ac.uk
Ramit has a background in electrical engineering and computational social sciences, with a MPhil and a PhD from the University of Cambridge as a Gates Scholar. He is a Fellow and Director of Studies of Churchill College. He was awarded the inaugural Cambridge Zero Fellowship.
Research
Ramit's research advances computational social science methodologies for climate and environmental sustainability, see here: https://www.collectivedesign.group.cam.ac.uk
Ramit serves as an Associate Editor for npj Climate Action (Nature), Energy Research and Social Sciences (Elsevier), Humanities and Social Science Communications (Nature) and PLOS Global Health. He is editorial board member for Cell Press's iScience.
Ramit receives research funding from the UKRI EPSRC and ESRC, the MasterCard Foundation, the Minderoo Foundation, and others. His research outputs regularly appear in Nature, Nature Climate Change, Nature Human Behaviour, Royal Society Transactions, amongst others.
Publications
Full list of papers: https://www.collectivedesign.group.cam.ac.uk/publications.html
Debnath, R. , Alvarez, R.M., and Ebanks, D. (2025). Why publishing referee reports could backfire on public trust. Nature, https://doi.org/10.1038/d41586-025-02317-z
Chen, T., and Debnath, R. (2025). The need of explainability in low-carbon urban system design using AI: A systematic review. Machine Learning: Earth. https://doi.org/10.1088/3049-4753/adde60
Cologna, V. et al. (2025) Extreme weather event attribution predicts climate policy support across the world. Nature Climate Change. https://doi.org/10.1038/s41558-025-02372-4
Seshadri, A., Gambhir, A., and Debnath, R. (2025). Navigating Systemic Risks in Low-Carbon Energy Transitions in an Era of Global Polycrisis. Global Sustainability , Cambridge University Press. https://doi.org/10.1017/sus.2025.7
Cologna, V et al. (2025) Trust in scientists and their role in society across 68 countries. Nature Human Behaviour, https://doi.org/10.1038/s41562-024-02090-5
van Daalen, K.R.,et al., (2024), Bridging the gender, climate, and health gap: the road to COP29 . The Lancet Planetary Health, https://doi.org/10.1016/S2542-5196(24)00270-5
Debnath, R., (2024). Communicating my value . Science, Vol 385, Issue 6710. https://doi.org/10.1126/science.ziylh46
Nielsen, K.S., et al., (2024), Underestimation of personal carbon footprint inequality in four diverse countries . Nature Climate Change, https://doi.org/10.1038/s41558-024-02130-y
Debnath, R., Creutzig, F., Sovacool, B.K., and Shuckburgh, E. (2023). Harnessing human and machine intelligence for planetary-level climate action. npj Climate Action, Nature. https://doi.org/10.1038/s44168-023-00056-3
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
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
Teaching and Supervisions
Course leader: Paper 1.5 Math and Programming (Year 1) Design Tripos
MAUS: Research Methods
MPP - Fundamentals of ML for public policy (POLIS/BIPP)
Ramit supervises undergrad, MPhil and PhD students, see current student list here: https://www.collectivedesign.group.cam.ac.uk/team.html
Other Professional Activities
Panel member - UKRI, NSF (USA), NSF (Swiss), EU Horizon
Member - EDITS, IIASA; Climate Social Science Network (Brown University)
Departmental level - Chair of IT Committee; Degree Committee
University level - Steering committee member (Centre for Human-Inspired AI; Cambridge Centre for Data-driven Discovery, and Cambridge Centre for Climate Repair) and Cambridge Zero.
