Dr Husein Perez
Dr. Husein Perez joined the School of the Built Environment in January 2019 as a Research Fellow in Construction Informatics. He obtained his PhD in Scientific Computing from Oxford Brookes University in 2016 in the School of Engineering Computing and Maths.
Prior to joining Brookes University as a research fellow in construction informatics, Dr. Perez worked as a Technical Consultant for Wolfram Research Europe and as R&D Scientist in Computer Vision at Fuel3D. He has a special interest in Machine Learning, particularly, in Deep Learning, Convolutional Neural Networks and in Computer Vision. His research is devoted to the application of artificial intelligence and machine learning techniques in the construction domain with a particular focus on automated building defects detection.
Teaching and supervision
- Research Design
- Applied Research Methods
- Using Generalised method of moments (GMM) for Panel Models to Investigate EPC ratings and Transaction Prices in the UK.
- Deep Learning driven Internet of Things (IoT) with Edge Computing for Energy Efficiency.
- Autonomous Robotic Systems Navigation Using Deep Learning for Indoor / Outdoor Environmental Awareness.
- NLP for Automated Valuation Models (AVM)
- Automatic cost estimation for “as-built” models by fusing machine learning and multi-view stereo 3D Reconstruction
Perez H, Joseph JHM, 'Deep learning Smartphone Application for Real-Time Detection of Defects in Buildings'
Structural Control and Health Monitoring 28 (7) (2021)
ISSN: 1545-2255 eISSN: 1545-2263Abstract Published here
Perez H, Joseph JHM, 'Improving the Accuracy of Convolutional Neural Networks by Identifying and Removing Outlier Images in Datasets Using t-SNE'
Mathematics 8 (5) (2020)
ISSN: 2227-7390Abstract Published here Open Access on RADAR
Husein Perez, Joseph H. M. Tah, Amir Mosavi, 'Deep Learning for Detecting Building Defects Using Convolutional Neural Networks'
Sensors 19 (16) (2019)
ISSN: 1424-8220Abstract Published here Open Access on RADAR