publications

2025

1. Multi-Robotic System for Welded Steel Disassembly

   Zain Karsan, Benjamin Dillenburger, and Catherine De Wolf

   In ARCHITECTURAL INFORMATICS - Proceedings of the 30th CAADRIA Conference, Mar 2025
2. Graph Based Disassembly Sequencing with Structural and Stability Constraints

   Zain Karsan, Benjamin Dillenburger, and Catherine De Wolf

   In Proceedings of the 2025 European Conference on Computing in Construction, Jul 2025

   Abs

   Disassembly is an important strategy in achieving material circularity and closing the loop in material flow. While disassembly sequencing is heavily studied in manufacturing, few examples consider the constraints present in construction. To address this gap we propose a graph based method for disassembly sequencing with constraints on stability and internal stress. We test our algorithm on three frame structures of increasing complexity and element count using construction specific heuristics to determine source nodes and disassembly direction. Our algorithm can compute feasible disassembly sequences with sufficient speed to support applications in online robotic path planning.

2024

1. Vision Assisted Robotic Plasma Cutting Setup for On-Site Disassembly of Welded Steel Structures

   Zain Karsan, Catherine De Wolf, and Benjamin Dillenburger

   Jul 2024

   DOI

2023

1. Desk Mate: A Collaborative Drawing Platform

   Zain Karsan

   In , Jul 2023

   Abs DOI

   Machine Learning (ML) in architecture is an emerging field with myriad potentials to impact the design process. Despite its many possibilities, ML is typically employed when the design problem is sufficiently defined, and further, is only integrated within software environments. Desk Mate is collaborative drawing machine that can be used early in the design process by coupling tangible tools like pens and trace paper with ML driven feedback and generation. Embedding physical tools that are familiar and intuitive with digital intelligence offers designers new ways of engaging with ML algorithms interactively, potentially changing the way the architectural industry approaches design problems. Desk Mate chains together image retrieval methods from machine vision with generative ML models like variational autoencoders (VAE) and generative adversarial networks (GANS) to react to design sketches as they are drawn. This pipeline allows Desk Mate to iterate through designs with the designer. Thus, Desk Mate demonstrates an interactive platform that collocates designer and machine as creative agents, facilitating drawing with ML driven feedback, potentially accelerating design iteration in the early stages of ideation.

2. Liquid Metal Printing

   Zain Karsan, Kimball Kaiser, Jared Laucks, and 1 more author

   In Proceedings of the 43rd Annual Conference for the Association for Computer Aided Design in Architecture (ACADIA), Jul 2023

2021

1. TinyZ: A Desktop CNC Machine to Enable Remote Digital Fabrication

   Zain Karsan

   In Realignments: Towards Critical Computation [Proceedings of the 41st Annual Conference of ACADIA], Oct 2021