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Department of Computer Science and Technology

  • Inaugural Cambridge Zero Fellow
  • Visiting Assistant Professor
  • Churchill College and Royal Statistical Society Fellow

Dr Ramit Debnath is currently a university assistant professor and inaugural Cambridge Zero fellow at the University of Cambridge, and a visiting faculty associate at Caltech's Humanities and Social Sciences division. He leads the Cambridge Collective Intelligence & Design Group.


At CST, Ramit is leading a research project on improving public understanding of climate action using social data science with Prof. Emily Shuckburgh, funded by Quadrature Climate Foundation. 

Ramit seeks to understand what is desirable machine intelligence for climate action. He uses design thinking, justice theory, NLP, machine learning and AI to reduce misinformation, recover trust and remove skepticism. His broader goal is to improve public understanding of climate change. He is the recipient of the 2022 Google Cloud Climate Innovation Challenge and the Postdoctoral Alan Turing Enrichment Award. His research has appeared in TIME, WIRED, CNN, and several other prominent media outlets (More info).

Ramit publishes extensively on solving society's wicked problems (Google Scholar). He has a background in electrical engineering and sustainable development and an MPhil-PhD as a Gates scholar from the University of Cambridge.


  • Computational Social Science for climate action and sustainability 
  • Climate justice and Social tipping points 
  • Fairness, Accountability and Transparency (FAccT) and human-in-the-loop AI
  • Polarization and misinformation 
  • Data science, design thinking and public policy

I share affiliations with multiple research units across Cambridge and Caltech for collaborative work. It includes the Energy Policy Research Group (CJBS), Bennett Institute of Public Policy (POLIS), Centre for Climate Repair (Engineering/DAMPT), Cambridge Social Decision-making Lab (Psychology), Centre for Natural Materials Innovation (Architecture) and Alvarez's Group (Caltech HSS).


  • Mathematics and Computing for Design Thinking, Design Tripos (Course leader), Architecture
  • Fundamentals of Machine Learning for Public Policy, Bennett Institute for Public Policy, POLIS
  • Research Methods, MPhil in Architecture and Urban Studies, Architecture


  • PhD programs 
  • MRes - PhD AI for Environmental Risks, CDT
  • MPhil in Engineering for Sustainable Development, Department of Engineering
  • MSt in AI Ethics and Society, Leverhulme Centre for the Future of Intelligence
  • MPhil in Architecture and Urban Studies, Department of Architecture 
  • Summer internship, Centre for Climate Repair, Department of Engineering
  • Volunteer supervisor, International Solar Energy Alliance 

Professional Activities



Showing selected papers. A full list of publications can be referred to here:

  • 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
  • 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 
  • Bardhan, R., Debnath, R., and Mukherjee, B. (2023). Factor in gender to beat the heat in impoverished settlements, Nature.
  • 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 Portfolio
  • Debnath, R., Bardhan, R., and Bell, M.L., (2023) Lethal heatwaves are challenging India’s sustainable development, PLOS Climate,
  • Debnath, R., Reiner, D. M., Sovacool, B. K., Müller-Hansen, F., Repke, T., Alvarez, R. M., & Fitzgerald, S. D. (2023). Conspiracy spillovers and geoengineering. iScience, Cell Press, 106166. 

  • 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 

  • Debnath, R., Bardhan, R., Shah, D.U., Mohaddes, K., Ramage, M.H., Alvarez, RM., and Sovacool, BK (2022) Social media enables people-centric climate action in the hard-to-decarbonise building sector. Scientific Reports, Nature Publishing 

  • Peng, Z., Debnath, R., Bardhan, R., and Steemers, K., (2022) Machine learning-based evaluation of dynamic thermal-tempering performance and thermal diversity for 107 Cambridge courtyards. Sustainable Cities and Society, Elsevier,  

  • Debnath, R., Bardhan, R., Misra, A., Hong, T., Vida, R., Ramage, M.H. (2022) Lockdown impacts on residential electricity demand in India: A data-driven and non-intrusive load monitoring study using Gaussian mixture models. Energy Policy, Elsevier 

  • Debnath, R., Bardhan, R., Reiner, D. M., and Miller, JR (2021) Political, Economic, Social, Technological, Legal and Environmental dimensions of electric vehicle adoption in the United States: A social-media interaction analysis. Renewable and Sustainable Energy Reviews, Elsevier.

  • Debnath R. and Bardhan R., (2020) India nudges to contain COVID-19 pandemic: a reactive public policy analysis using machine-learning based topic modelling, PLOS ONE. 

  • Debnath, R., Darby, S., Bardhan, R., Mohaddes, K., & Sunikka-Blank, M. (2020). Grounded reality meets machine learning: A deep-narrative analysis framework for energy policy research. Energy Research & Social Science, Elsevier

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