The ISPRS SC Webinar Series
ISPRS IV/2 Webinar: Predicting Real Estate Prices with Machine Learning – A Practical View
by Christopher Kmen, PhD
June 27, 2025 | 8:00 am GMT+0 (10:00 am CET)
This webinar is organised by the ISPRS WG IV/2 with technical support from the ISPRS Student Consortium. Here are the details for the webinar:
Date: June 27, 2025 | 8:00 am GMT+0 (10:00 am CET)
Speaker: Christopher Kmen, PhD
Abstract:
Machine learning and deep learning offer a wide range of applications in many industries. This seminar will demonstrate the utilization of these models in the analysis of the real estate market, employing large-scale transaction data to construct models of spatial and temporal price dynamics. The presentation will demonstrate the use of geographic, infrastructural, and socio-demographic characteristics for price forecasting and the impact of decisions regarding the data to be modeled. The presentation shows how these models can be used in transfer learning processes, in which models trained in data-rich cities are transferred to data-sparse cities. The models were evaluated using human subject experiments in which the models were compared to expert predictions.
Speaker's Bio:
Christopher Kmen received a BSc and MSc in Geodesy and Geoinformation from TU Wien in 2017 and 2018. Since 2021, he has been a PhD student in Geoinformation at TU Wien, researching spatial machine learning and deep learning. From 2018 to 2024, he was employed as a research and senior analyst in the real estate industry. In 2025, he assumed the role of senior data science consultant, leading initiatives involving machine learning-supported market models, GIS workflows, and data quality initiatives. His current research interests include spatial machine learning and deep learning techniques with a particular focus on time-based regression models in the real estate sector.
