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.

Projects

[2022 - 2023]: Principal Investigator, Digital or Data Social Science Approaches to Net Zero

[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.

Grants

[2022 - 2023]: Principal Investigator, Digital or Data Social Science Approaches to Net Zero ESRC Policy Fellowship with the Department for Energy Security and Net Zero (DESNZ)

[2022]: National Centre for Research Methods (NCRM) Bursary for Training for attending the Reproducibility Bootcamp.

[2021]: Researcher Co-Investigator in the Natural Environment Research Council funded ‘EMPOWER: Empowering citizen and community adaptation to systemic risks from climate change’Link opens in a new window project

[2021]: ESRC Festival of Social Science (FOSS) funding for ‘Empowering Communities to Fight Climate Change: What is Amiss?’ – an interactive online workshop and public seminar to explore how communities manage external shocks for sustainable resource management

[2020]: Building Research Culture competition funding awarded by the Doctoral College at University of Surrey for organising and running the Surrey Research Dating Forum.

Teaching

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

Publications

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

Science Communication

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).