Dr Sandhya Patidar

I am a Research Associate working on the 'Low Carbon Future project' in collaboration with staff in the Department of Actuarial Mathematics and Statistics (School of Mathematical and Computer Sciences), and in the School of the Built Environment.

I am responsible mainly for research activities and to supervise students working on the research projects (MSc/PhD).

My research interests include the application of statistical methods in data analysis and modelling. In particular, I am developing a simple statistical tool to perform dynamic building simulations for existing and new buildings in future probabilistic climate (Climate Information available from the latest UK climate projections programme (UKCP09).

I am also interested in time-series analysis, stochastic processes, coupled nonlinear dynamical system driven by Gaussian white noise and their control, bifurcation and chaos theory.

I studied my PhD in applied Mathematics from Loughborough University in May 2009 and since then I am working as Research Associate in School of Mathematical and Computer Sciences (Actuarial Mathematics and Statistics) at Heriot-Watt University.

My research project at Heriot-Watt University is part of the Adaptation and Resilience to Climate Change Programme (ARCC).

My role is to develop a computationally efficient and user friendly statistical tool that could perform building thermal simulations for thousands of available future probabilistic climate (UKCP09). Outputs of the project should provide building design community and stakeholders with a decision support tool for adequately sizing HVAC (heating, ventilating, and air-conditioning) plant and equipment in buildings.

My PhD work demonstrates the possibility of controlling (Pyragas delayed feedback) noise induced global dynamics in stochastic neural networks modeled as a system of a large number of identical excitable FitzHugh-Nagumo oscillators coupled via the mean field.

• S. Patidar, D. P. Jenkins, G. J. Gibson, P. F. G. Banfill, Statistical techniques to emulate dynamic building simulations for overheating analyses in future probabilistic climates, Journal of Building Performance Simulation, 1-14, iFirst article, 2011.
• S. Patidar, A. Pototsky and N.B. Janson, Controlling noise-induced behavior of excitable networks, New J. Phys. 11 073001 (2009).
• D. P. Jenkins, S. Patidar, G. J. Gibson, P. F. G. Banfill, Incorporating future probabilistic climate projections into dynamic building simulation, Energy and Buildings, in correspondence.
• S.Patidar, D. P. Jenkins, P. F. G. Banfill, G. J. Gibson, Simple Statistical Model for Complex Probabilistic Climate Projections: Overheating Risk and Extreme Events, Climate Change Issues, World Renewable Energy Congress 2011- Sweden, 8 – 11 May 2011 (accepted for publication).
• D. P. Jenkins, S. Patidar, G. J. Gibson, P. F. G. Banfill, Translating Probabilistic climate predictions for use in building simulation. In F.Nicol, ed. Proceedings of Conference, Adapting to change: new thinking on comfort. Cumberland Lodge, Windsor, UK, 9 – 11 April 2010. Available from: http://nceub.commoncense.info/uploads/64-01-13-Jenkins.pdf