C.C.J. van Engelenburg
C.C.J. van Engelenburg
Profiel
Architects communicate their designs through various visual abstractions of the physical space; including orthographic drawings, photos, and 3D models. Semantic similarity learning for architectural drawings is a PhD project of Casper van Engelenburg that started in October 2021, focusing on understanding visual patterns in floorplan image data. He develops deep contrastive learning frameworks that enable us to learn low-dimensional, task-agnostic representations of architectural drawings. This research line builds a foundation for large quantitative analysis of archival and linked visual data. Besides theoretical work, his aim is to connect it to the practice by enhancing Architectural-specific search engines.
Expertise
Publicaties
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2024
AI-supported approach for human-building interaction implemented at furniture scale
Henriette Bier / Arwin Hidding / Stijn Brancart / Alessandra Luna-Navarro / Seyran Khademi / Casper van Engelenburg
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2024
Advancing Applications for Artificial-Intelligence-Supported Ambient Control in the Built Environment
Henriette Bier / Arwin Hidding / Seyran Khademi / Casper van Engelenburg / Hamed Alavi / Sailin Zhong
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2024
Advancing Sustainable Approaches in Architecture by Means of Design-to-Robotic-Production
Henriette Bier / Arwin Hidding / Casper van Engelenburg / Tarique Ali
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2024
Computer Vision for Terrain Mapping and 3D Printing In-situ of Extra/-terrestrial Habitats
Giuseppe Calabrese / Arwin Hidding / Henriette Bier / Casper van Engelenburg / Seyran Khademi / Atousa Aslaminezhad
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2024
Floor plan generation
The interplay among data, machine, and designer
Fatemeh Mostafavi / Casper van Engelenburg / Seyran Khademi / Georg Vrachliotis -