Mr Hamid Nejadghorban
Research Fellow in Econometric Modelling for Energy and the Environment
Bartlett School Env, Energy & Resources
Faculty of the Built Environment
- Joined UCL
- 10th Feb 2022
Assistant Lecturer, University of Essex:
Department of Mathematical Science:
MA318: Statistical Methods and MA108: Statistics I.
Department of Economics:
EC352: Econometrics Methods, EC252: Introduction to Econometric Methods, EC251: Mathematical Methods in Economics, EC111: Introduction to Economics.
Hamid Nejadghorban is a Research Fellow at the UCL Institute for Sustainable Resources and a Doctoral Researcher in the Department of Economics at the University of Essex. Hamid focuses on machine learning and quasi-experimental analysis of micro energy data at the household level. Hamid is working on policy evaluation of energy schemes, such as the cross-cutting evaluation of BEIS’ Short-Term Economic Stimulus Scheme and Energy Bill Support Scheme.
In his PhD, Hamid is developing deep reinforcement learning (DRL) algorithms such as Twin Delayed Deep Deterministic Policy Gradients (T3D) for forecasting markets with high volatility. Previous work experience focused on applying machine learning algorithms to determine the optimal setting for energy-consuming appliances, air conditioners and boilers using big data.