Talks and Presentations

The Effects of the Thermal Environment on Sleep and Novel Control Solutions

June 25, 2026

PhD Forum Presentation, ACM Sustainability Week 2026 PhD Forum, Banff, Canada

This PhD Forum presentation outlined a dissertation on improving sleep in Singapore’s hot-humid residential context through technological and behavioural solutions. Situated within Project HEATS, the work focuses on how indoor thermal conditions affect sleep and on developing occupant-centric control approaches for real homes. The talk organized the research around two field studies already underway, with a third phase on novel personal comfort modeling still in development.

Scalable Adaptive AC Control in Real Sleep Environments

June 23, 2026

Conference Presentation, ACM BuildSys'26, Banff, Canada

This conference talk presented a deployable research prototype for reinforcement learning (RL) based bedroom air-conditioning (AC) control in real homes. Sleep thermal comfort is dynamic and guided by a shifting neutral thermal sensation, and the setpoint profiles required for comfortable sleep can vary across nights. While RL has shown promise for personalized AC control, no field-deployable RL research prototype had previously been reported for residential sleep environments.

Just-in-Time Adaptive Interventions (JITAI) to Improve Indoor Air Quality in Sleep Environments

June 16, 2026

Conference Presentation, Indoor Air 2026, Singapore

This conference talk presented a pilot study on Just-in-Time Adaptive Interventions (JITAIs) for improving indoor air quality (IAQ) in sleep environments. JITAIs are context-aware recommendation systems originally developed in mobile health to deliver timely, personalized support for self-management. The talk examined whether the same approach can nudge occupants toward indoor setting adjustments, such as window opening, in the built environment.

Text-Mining-Driven Review of Recommender Systems and Reinforcement Learning for Building Control and Occupant Interaction

November 05, 2024

Presentation, BUDS Lab, Singapore

This invited talk explored the application of text-mining techniques in conducting literature reviews, with a focus on the integration of recommender systems and reinforcement learning for smart building control and occupant interaction. Text-mining was presented as a powerful alternative to conventional literature review methods, enabling the analysis of large volumes of academic publications with improved efficiency and reduced subjectivity.

Invited Talk at China Academy of Building Research (CABR) on “The Opportunities and Challenges of Reinforcement Learning for Smart Building Control”

June 10, 2022

Talk, China Academy of Building Research, Shanghai, China

Reinforcement learning (RL) emerged as a transformative approach for optimizing smart building control systems, offering dynamic and adaptive solutions that significantly enhanced energy efficiency, occupant comfort, and operational sustainability. In this invited talk, the speaker delved into the evolving role of RL in the context of smart building technologies, emphasizing its potential to revolutionize how buildings responded to environmental conditions, occupancy patterns, and energy demands.

Energy Efficient Operation Optimization of Building Air-conditioners via Simulator-assisted Asynchronous Reinforcement Learning

December 02, 2021

Conference Presentation, 3rd International Conference on Resources and Environmental Research (ICRER 2021), Xiamen, China

The presented study explored a reinforcement learning (RL)-based strategy for optimizing the energy-efficient operation of variable refrigerant flow (VRF) air-conditioners in office settings. The research addressed the significant energy consumption of air-conditioning systems, which account for a substantial proportion of building energy usage, and proposed an innovative solution using asynchronous reinforcement learning coupled with detailed building energy simulation models.

Wenhao Zhang