I am a Teaching Fellow in Statistics the School of Psychology, Philosophy and Language Sciences (PPLS) at University of Edinburgh. I support the running of statistics courses across undergraduate degrees and currently developing learning materials in statistics using R that can be used by wider social science communities.
My PhD research was concerned with big data analysis in application to social science research questions. In my thesis I analysed data recorded by smart meters to study energy users behavioural patterns as well as I address the challenges presented in these kind of complex time series data structures. The motivation behind my work was to explore whether there is a potential for big data to inform public policy and decision making in energy sector. I used computational statistics methods to answer these questions.
In the past I worked as Teaching Fellow in Quantitative Methods at UCL School of Public Policy. I also provided an assistance with teaching across Q-Step undergraduate courses in statistics for social science.
My research and teaching interests are spanned broadly across the area of quantitative methods in interdisciplinary settings: social sciences, data science and energy research, I am keen to explore new forms of data and novel methods and technology that can be used to analyse it and passionate about both development and application of statistical methods as well as promoting those to new generation of interdisciplinary researchers through active involvement in teaching and training activities.
Blog Post for ‘Teaching Matters’ University of Edinburgh
Seminar at UCL Energy Institute: