Kavin Narasimhan (Assistant Professor)
My research focuses on computational modelling for public policy using methods like agent-based modelling, causal loop diagramming, network mapping and analysis. I am also interested in knowledge co-production using participatory research methods.
PhD in Computer Science from Queen Mary University of London and Bachelor of Engineering (B.E.) in Computer Science and Engineering from Anna University, India. Awarded Fellow of The Higher Education Academy (FHEA) in 2021. Between 2015-2023, I was a Research Fellow in the Centre for Research in Social Simulation (CRESS) at the University of Surrey.
[2018-2021]: Led the development of the WATER user associations at the Interface of Nexus Governance (WATERING) model in the FutureDAMS project.
[2015 - 2017]: Led the development of the HOuseholds and Practices in Energy-use Scenarios (HOPES) model in the WholeSEM project.
At CIM, I teach on the following modules
- IM952: Big Data Research: Hype or Revolution?
- IM939: Data Science Across Disciplines: Principles, Practice and Critique
- IM949: Data Visualisation in Science, Culture and Public Policy
Oliver, T. H., Bazaanah, P., Da Costa, J., Deka, N., Dornelles, A. Z., Greenwell, M. P., Nagarajan, M., Narasimhan, K., Obuobie, E., & Osei, M. A. (2023). Empowering citizen-led adaptation to systemic climate change risks. Nature Climate Change, 1–8.
Johansson,E., Nespeca, V., Sirenko, M., van den Hurk, M., Thompson, J., Narasimhan, K., Belfrage, M., Giardini, F. and Melchior, A. (2023) A Tale of Three Pandemic Models: Lessons Learned for Engagement with Policy Makers Before, During, and After a Crisis. Review of Artificial Societies and Social Simulation, 15 Mar 2023. https://rofasss.org/2023/05/15/threepandemic
Narasimhan, K., Leoni, S., Luckner, K., Carpentras, D. and Davis, N. (2022) ESSA@work: Reflections and looking ahead. Review of Artificial Societies and Social Simulation, 20 Feb 2023. https://rofasss.org/2022/02/20/essawork
Narasimhan, K and Gilbert, N. (2022). Reusable Components for an Agent-based Model of Irrigation Management. International Congress on Environmental Modelling and Software. 24. https://scholarsarchive.byu.edu/iemssconference/2022/Online_and_Poster_Presentations/24
Narasimhan, K., Gilbert, N., & Elsenbroich, C. (2022). WATERING Crop Growth Reusable Building Block (1.0). Zenodo. https://doi.org/10.5281/zenodo.6323653
Narasimhan, K., Gilbert, N., & Elsenbroich, C. (2022). WATERING Irrigation Reusable Building Block (1.0). Zenodo. https://doi.org/10.5281/zenodo.6323633
Narasimhan, K., Gilbert, N., & Elsenbroich, C. (2020). An Integrated Model to Assess the Impacts of Dams in Transboundary River Basins. 321–327.
Gilbert, N., Ahrweiler, P., Barbrook-Johnson, P., Narasimhan, K. P., & Wilkinson, H. (2018). Computational modelling of public policy: Reflections on practice. Journal of Artificial Societies and Social Simulation, 21(1).
Narasimhan, K., Gilbert, N., Hope, A., & Roberts, T. (2018). Demystifying energy demand using a practice centric agent-based model.
Narasimhan, K., Roberts, T., Xenitidou, M., Gilbert, N. (2017). Using ABM to Clarify and Refine Social Practice Theory. In: Jager, W., Verbrugge, R., Flache, A., de Roo, G., Hoogduin, L., Hemelrijk, C. (eds) Advances in Social Simulation 2015. Advances in Intelligent Systems and Computing, vol 528. Springer, Cham. https://doi.org/10.1007/978-3-319-47253-9_27
Narasimhan, K., Roberts, T., & Gilbert, N. (2016). Using agent-based modelling to understand the spread of energy consuming social practices in households. 13–15. http://www.demand.ac.uk/wp-content/uploads/2016/03/DEMAND2016_Full_paper_9-Narasimhan.pdf
Narasimhan, K. P. (2016). Computational Proxemics: Simulation-based analysis of the spatial patterns of conversational groups. https://qmro.qmul.ac.uk/xmlui/handle/123456789/23843
I enjoy teaching computer science and agent-based modelling courses and actively engage in research outreach initiatives (watch about our research on household energy use and community based water governance on YouTube).
Centre for Interdisciplinary Methodologies (CIM)
University of Warwick
Coventry CV4 7AL