CIBSE is the prime source of expertise in the Building Services industry, and the President’s Prize recognises work that displays a distinguished understanding and knowledge of the field, as well as excellent visual information. Yu is the first Chinese winner of the prize. A trophy was also awarded to UNNC as acknowledgement of its achievement.

In his thesis, Yu innovatively adopted machine learning and data-driven approaches to analyse and model a room occupant’s window opening behaviours based on statistics from 95 cities in China covering all climate zones.

“The accuracy of model predictions turns out to be about 95.4%, which means that the model enables the users to estimate window openings directly from weather conditions,” said Yu. “It is rare to use artificial intelligence in building services to predict human behaviours, but I think green architecture - high comfort with low energy - is the trend. Therefore, the methods I adopted can have wider applications in similar circumstances to maximise people’s indoor comfort.”

Driven by great passion for the field, Yu paid great attention to the project. “During the whole semester, I only left campus three times and spent almost all of my weekends researching. So the prize is of great significance to me. Thanks to my tutor, Dr Zhou, who was always there to provide help, I overcame all those difficulties,” said Yu.

The time management and learning abilities of Yu were what impressed Dr Zhou, Assistant Professor in Building Service Engineering and Building Physics. Yu finished his thesis almost three months before many other students, and studied machine learning by himself for it.

Now studying for a Master’s at the University College London, Yu describes himself as ordinary. “There is a sign on campus saying that we have to pay 100% effort for even 1% hope of achievement. This is the most important lesson I learnt at UNNC.”

After his studies, Yu intends to delve into data science and make his own future contribution to urban planning and green architecture.