I am a Research Fellow in the Centre for Research in Social Simulation (CRESS) at the Department of Sociology. I am currently leading the development of the WATER user associations at the Interface of Nexus Governance (WATERING) model in the FutureDAMS project. I previously led the development of the HOuseholds and Practices in Energy-use Scenarios (HOPES) model in the WholeSEM project.
My research area and expertise is in using agent-based modelling and data analytics to explore, understand and evaluate human behaviour, interactions and decison-making in day-to-day contexts. There is a wide range of real-world applications to my research in the areas of climate change mitigation, adaptation, UN Sustainable Development Goals and related policy-making.
I have a PhD in Computer Science (passed with No Corrections) from Queen Mary University of London and a Bachelor of Engineering (B.E.) degree in Computer Science and Engineering (passed first class with distinction) from Anna University, India. I achieved the status of Fellow of The Higher Education Academy (FHEA) in 2021.
I did my PhD in the Cognitive Science Research Group at the School of Electronic Engineering and Computer Science, Queen Mary University of London. My thesis titled Computational Proxemics: Simulation-based analysis of the spatial patterns of conversational groups can be found here
I worked for Tata Consultancy Services (India) and some startup companies in the UK as a web developer between 2008 to 2014. While studying at QMUL, I was a member of GHack
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).
If you are interested in finding out more about these projects or discuss about collaborations, please drop me a line or get in touch on Twitter.
Areas of specialism
Computational models are increasingly being used to assist in developing, implementing and evaluating public policy. This paper reports on the experience of the authors in designing and using computational models of public policy (‘policy models’, for short). The paper considers the role of computational models in policy making, and some of the challenges that need to be overcome if policy models are to make an effective contribution. It suggests that policy models can have an important place in the policy process because they could allow policy makers to experiment in a virtual world, and have many advantages compared with randomised control trials and policy pilots. The paper then summarises some general lessons that can be extracted from the authors’ experience with policy modelling. These general lessons include the observation that often the main benefit of designing and using a model is that it provides an understanding of the policy domain, rather than the numbers it generates; that care needs to be taken that models are designed at an appropriate level of abstraction; that although appropriate data for calibration and validation may sometimes be in short supply, modelling is often still valuable; that modelling collaboratively and involving a range of stakeholders from the outset increases the likelihood that the model will be used and will be fit for purpose; that attention needs to be paid to effective communication between modellers and stakeholders; and that modelling for public policy involves ethical issues that need careful consideration. The paper concludes that policy modelling will continue to grow in importance as a component of public policy making processes, but if its potential is to be fully realised, there will need to be a melding of the cultures of computational modelling and policy making.
Conference Proceedings and Working Papers
Narasimhan K., Gilbert N., Elsenbroich C. (2020) An Integrated Model to Assess the Impacts of Dams in Transboundary River Basins. In: Verhagen H., Borit M., Bravo G., Wijermans N. (eds) Advances in Social Simulation. Springer Proceedings in Complexity. Springer, Cham. DOI: 10.1007/978-3-030-34127-5_31
Narasimhan, K., Gilbert, N., Hope, A., & Roberts, T. (2017). Demystifying Energy Demand using a Practice-centric Agent-based Model. Link to working paper.
Narasimhan, K., Roberts, T., Xenitidou, M., & Gilbert, N. (2017). Using ABM to clarify and refine social practice theory. In Advances in Social Simulation 2015 (pp. 307-319). Springer, Cham. DOI: 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. In DEMAND Centre Conference.