Area of research
Building and Construction · Environmental Engineering
Research interest
Research interests include Environmental science, Urban heat island, Radiative cooling, Climatology, Daytime, and Energy consumption.
A probabilistic framework for predicting spatiotemporal intensity and variability of outdoor thermal comfort
Rooftop photovoltaic solar panels warm up and cool down cities
Systematic review of the efficacy of data-driven urban building energy models during extreme heat in cities: Current trends and future outlook
Recent Advances in Fluorescence-Based Colored Passive Daytime Radiative Cooling for Heat Mitigation
Coloured radiative cooling materials in the built environment parallel the cooling benefits of white conventional surfaces and balanced winter performance
Integrated Assessment of Urban Overheating Impacts on Human Life
Development of a heat stress exposure metric – Impact of intensity and duration of exposure to heat on physiological thermal regulation
The health benefits of greening strategies to cool urban environments – A heat health impact method
On the energy modulation of daytime radiative coolers: A review on infrared emissivity dynamic switch against overcooling
Dynamic impact of climate on the performance of daytime radiative cooling materials
Upscaling of SMA film-based elastocaloric cooling
Occupancy-based zone-level VAV system control implications on thermal comfort, ventilation, indoor air quality and building energy efficiency
Predicting the magnitude and the characteristics of the urban heat island in coastal cities in the proximity of desert landforms. The case of Sydney
Green and cool roofs’ urban heat island mitigation potential in tropical climate
Using artificial neural networks to assess HVAC related energy saving in retrofitted office buildings
Analyzing the heat island magnitude and characteristics in one hundred Asian and Australian cities and regions
LOCAL CLIMATE CHANGE AND URBAN HEAT ISLAND MITIGATION TECHNIQUES – THE STATE OF THE ART
Forecasting diurnal cooling energy load for institutional buildings using Artificial Neural Networks
Review of occupancy sensing systems and occupancy modeling methodologies for the application in institutional buildings