AI-enhanced Automated and Large-scale Real Estate Valuation

House price valuation and forecasting are considered as critical urban problems that aid individuals and organizations to execute a variety of property-related practices such as property purchase and selling, taxation, and mortgage property. This project aims to collect appropriate features for house price modeling and to develop a combined machine learning-graph modeling approach to have an accurate property value assessment model. Then, a spatial-temporal prediction model based on deep learning is designed for future house price forecasting. The intern involved in this project encounters a real-world project with plenty of practical instructive experiences. Additionally, he can attain a priceless experience of working on industry research. The partnering academic institutions will gain valuable insight into new and accurate house price modeling and prediction, which is one of the most trending real estate problems.

Faculty Supervisor:

Zheng Liu

Student:

Amirhossein Zaji

Partner:

Offerland

Discipline:

Engineering

Sector:

University:

Program:

Accelerate