CIB seeks to advance built environment research by recognizing and rewarding outstanding work of emerging researchers. As a result, a Best Doctoral Dissertation award is presented annually to recognize researchers whose PhD has been judged to be of excellent quality. This is the fourth year of the award.
Shortlisted candidates for the CIB Best Doctoral Dissertation award 2024 are invited to introduce their work, through short presentations, to an Awards Committee appointed by the CIB Board. The 2024 Best Doctoral Dissertation award presentations will take place online on Tuesday 19th November at 8pm EET. CIB members are invited to join the presentation event to hear the excellent work being done by those who we anticipate have the potential to make major contributions to the built environment in the future.
Candidates
The shortlisted candidates for the CIB Best Doctoral Dissertation award 2024 are:
- Dr. Hongying Zhao, RMIT University Student Chapter
- Dissertation title: Energy, Economic and Environmental Performances of BIPV Façade in Urban Environment: a Machine Learning Based Urban Morphology Method
- Dr. AniaKhodabakhshian – Politecnico di Milano Student Chapter
- Dissertation title: Machine Learning for Risk Management in Construction Projects
- Dr. De-Graft Joe Opoku – WSU Student Chapter
- Dissertation title: A methodology for digitally optimising energy consumption in buildings
- Dr. Olufisayo Adewumi Adedokun, Newcastle University Student Chapter
- Dissertation title: Incentives for Encouraging Householders’ Self-Evacuation from BushfireProne Areas in NSW, Australia
- Dr. Oluleye Ifeoluwa Benjamin, The Hong Kong Polytechnic University Student Chapter
- Dissertation title: Assessment model and decision support system for the adoption and implementation of circular economy in the building construction industry in Nigeria
Short introductory videos by some of the candidates are available below.
| PhD thesis – Machine Learning for Risk Management in Construction Projects – Ania Khodabakhshian Politecnico di Milano | | Incentives for Encouraging Householders Self-Evacuation from Bushfire-Prone Areas in New South Wales – Olufisayo Adedokun |
| Energy, Economic and Environmental Performances of BIPV Façade in Urban Environment: a Machine Learning Based Urban Morphology Method – Hongying Zhao | A methodology for digitally optimising energyconsumption in buildings – De Graft Joe Opoku |
