Area of research
Electrical and Electronic Engineering · Building and Construction
Research interest
Research interests include Computer science, Reinforcement learning, Control (management), Electrification, Flexibility (engineering), and Renewable energy.
SolNet: Open-source deep learning models for photovoltaic power forecasting across the globe
Dyna-PINN: Physics-informed deep dyna-q reinforcement learning for intelligent control of building heating system in low-diversity training data regimes
Creating synthetic energy meter data using conditional diffusion and building metadata
What-if: A causal machine learning approach to control-oriented modelling for building thermal dynamics
Ten questions concerning data-driven modelling and forecasting of operational energy demand at building and urban scale
Developing energy flexibility in clusters of buildings: A critical analysis of barriers from planning to operation
How good are TSO load and renewable generation forecasts: Learning curves, challenges, and the road ahead
Energy balances, thermal performance, and heat stress: Disentangling occupant behaviour and weather influences in a Dutch net-zero energy neighborhood
Towards data-driven energy communities: A review of open-source datasets, models and tools
Transfer learning in demand response: A review of algorithms for data-efficient modelling and control
Multi-agent reinforcement learning for modeling and control of thermostatically controlled loads
Electricity load-shedding in Pakistan: Unintended consequences, opportunities and policy recommendations
Determinants of energy flexibility in residential hot water systems
Teaching Robots a Lesson: Determinants of Robot Punishment
Gigawatt-hour scale savings on a budget of zero: Deep reinforcement learning based optimal control of hot water systems
Generalizable occupant-driven optimization model for domestic hot water production in NZEB