Professor Jo Zhong

Personal statement:

I am an Associate Professor specialising in sustainable built environments, building engineering services, and human‑centred climate resilience. My research integrates environmental data science, ageing and dementia, indoor environmental quality, and social equity. I work across engineering, public health, and policy to understand how buildings, neighbourhoods, and infrastructure shape wellbeing across the life course. My methods include mixed‑methods research, spatial analysis, environmental monitoring, and interdisciplinary systems modelling. I collaborate widely across Europe on climate adaptation, healthy ageing, and data‑enabled decision‑making for policy and practice.

Key topic areas of research or interest:

Sustainable Built Environment

Collaboration opportunities:

I welcome collaborations on environmental data science, ageing and dementia, indoor environmental quality, climate resilience, and health‑equity research. I am particularly interested in interdisciplinary partnerships linking engineering, public health, neuroscience, and policy. Opportunities include joint projects, co‑authored publications, data‑driven modelling, and work with local authorities or government agencies. I am open to consultancy, commissioned research, and media contributions related to sustainable buildings, healthy ageing, and climate adaptation.

Publications:

Shuqin Chen, Jianan Qian, Wangxi Gu, Yuhang Ma, Hua Zhong, Robust Configuration Optimisation of Low-Carbon Integrated Energy Systems under Variable Equipment Efficiency and Source-Load Uncertainty Conditions,Energy,2026,140046,ISSN:0360-5442, https://doi.org/10.1016/j.energy.2026.

Seyed Hamed Godasiaei, Obuks A. Ejohwomu, Hua Zhong, Douglas Booker, Interpretability in machine learning for IAQ and HVAC optimisation: A response to Oka et al, Building and Environment, Volume 284, 2025, 113494, ISSN 0360-1323, https://doi.org/10.1016/j.buildenv.2025.113494

Li, Gaomei, Huangwanjin Zhou, Jian Kang, Hua Zhong and Shen Xu. “Optimising Urban Energy Dynamics: A Multifactorial Approach to Building Energy Use and Solar Photovoltaic Power Generation in Urban Blocks.” Energy and Built Environment (2025): n. pag. https://doi.org/10.1016/j.enbenv.2025.07.002

Gao, H., Zhong, H. and Zou, L., 2025. Human-Centric IoT Control: A Framework for Quantifying the Impact of Occupant Behaviour on Energy Efficiency in Shared Offices. Journal of Building Engineering, p.112784. https://doi.org/10.1016/j.jobe.2025.112784

Godasiaei, S.H., Ejohwomu, O.A., Zhong, H. and Booker, D., 2025. Integrating Experimental Analysis and Machine Learning for Enhancing Energy Efficiency and Indoor Air Quality in Educational Buildings. Building and Environment, p.112874. https://doi.org/10.1016/j.buildenv.2025.112874