Artificial Intelligence and Data Integration

Research Area

ICD and its Chair for Computing in Architecture investigate applications of artificial intelligence (AI) for architecture, engineering, and construction, often in collaboration with researchers at the Max Planck Institute for Intelligent Systems and in Cybervalley. In optimization, we investigate and improve the performance of (multi-objective) optimization algorithms. In machine learning (ML), we investigate the use of ML in interactive design tools and visualizations, for example to predict the behavior of material systems. In symbolic AI, we investigate the integration of Knowledge Graphs and AI Planning into multi-disciplinary co-design workflows.

Related Research Projects

Towards Human-Robot Co-Agency

Multi-objective optimization and machine learning for climate-friendly building design

Computerbasierte Methoden und KI für die Planung klimaneutraler Gebäude

Modular Data Architecture for Preparation, Annotation and Exchange for Conceptual Design

Data Processing and AI for Predictive and Adaptive Co-Design

Task and Motion Planning for Collaborative Robotic Construction with Irregular Materials

Knowledge Representation for Multi-Disciplinary Co-Design

Innovative AI-based Sustainable Timber Construction Process Planning

Related Research Tools

Opossum

Selected Publications

  1. 2024

    1. Skoury, L., Treml, S., Opgenorth, N., Amtsberg, F., Wagner, H. J., Menges, A., & Wortmann, T. (2024). Towards data-informed co-design in digital fabrication. Automation in Construction, 158, 105229. https://doi.org/10.1016/j.autcon.2023.105229
    2. Kannenberg, F., Gil Pérez, M., Schneider, T., Staab, S., Knippers, J., & Menges, A. (2024). Bayesian Inference for Modelling Uncertainty in Non-Standard Building Systems. In P. Eversmann, C. Gengnagel, J. Lienhard, M. Ramsgaard Thomsen, & J. Wurm (Eds.), Scalable Disruptors. DMS 2024 (Proceedings of the Design Modelling Symposium 2024) (pp. 69--80). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-68275-9_6
    3. Abdelaal, M., Galuschka, M., Zorn, M., Kannenberg, F., Menges, A., Wortmann, T., Weiskopf, D., & Kurzhals, K. (2024). Visual analysis of fitness landscapes in architectural design optimization. The Visual Computer, 40(7), Article 7. https://doi.org/10.1007/s00371-024-03491-3
    4. Nakhaee, A., Elshani, D., & Wortmann, T. (2024). A Vision for Automated Building Code Compliance Checking by Unifying Hybrid Knowledge Graphs and Large Language Models. Design Modelling Symposium Berlin, 445--457.
    5. Zhang, R., Xu, X., Liu, K., Kong, L., Wang, W., & Wortmann, T. (2024). Airflow modelling for building design: A designers’ review. Renewable and Sustainable Energy Reviews, 197, 114380. https://doi.org/10.1016/j.rser.2024.114380
    6. Gomaa, H., Chau, W. M., Karazi, Y., Biala, E., Akbar, Z., Wortmann, T., & Ostermann, M. (2024). Influence of Geometry on Growth and Strength of 3D-Printed Mycelium Composites: A Data-Driven Study. In P. Eversmann, C. Gengnagel, J. Lienhard, M. Ramsgaard Thomsen, & J. Wurm (Eds.), Scalable Disruptors (pp. 331--345). Springer Nature Switzerland.
    7. Skoury, L., & Wortmann, T. (2024). Prediction Models for Co-Design in Industry 4.0. In P. Eversmann, C. Gengnagel, J. Lienhard, M. Ramsgaard Thomsen, & J. Wurm (Eds.), Scalable Disruptors. DMS 2024 (Proceedings of the Design Modelling Symposium 2024) (pp. 507–519). Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-68275-9_41
    8. Sardari, S., Sevim, S., Zhang, P., Ron, G., Leder, S., Menges, A., & Wortmann, T. (2024). Deep Agency - Towards human guided robotic training for assembly tasks in timber construction. In O. Kontovourkis, M. C. Phocas, & G. Wurzer (Eds.), Proceedings of the 42nd Conference on Education and Research in Computer Aided Architectural Design in Europe. Data-Driven Intelligence. (Vol. 1, pp. 193–202). eCAADe, University of Cyprus, Department of Architecture. https://papers.cumincad.org/data/works/att/ecaade2024_420.pdf
    9. Bauscher, E., Dai, A., Elshani, D., & Wortmann, T. (2024). Learning and Generating Spatial Concepts of Modernist Architecture via Graph Machine Learning. ACCELERATED DESIGN: Proceedings of the 29th International Conference on Computer-Aided  Architectural Design Research in Asia (CAADRIA), Volume1, 159–168.

  2. 2023

    1. Sherkat, S., Garmaroodi, A. A., Wortmann, A., & Wortmann, T. (2023). Residential complex design as a Constraint Satisfaction Problem. Automation in Construction, 154, 104995. https://doi.org/10.1016/j.autcon.2023.104995
    2. Elshani, D., Hernandez, D., Lombardi, A., Siriwardena, L., Schwinn, T., Fisher, A., Staab, S., Menges, A., & Wortmann, T. (2023). Building Information Validation and Reasoning Using Semantic Web Technologies. In M. Turrin, C. Andriotis, & A. Rafiee (Eds.), Computer-Aided Architectural Design. INTERCONNECTIONS: Co-computing Beyond Boundaries (pp. 470--484). Springer Nature Switzerland.
    3. Sherkat, S., Skoury, L., Wortmann, A., & Wortmann, T. (2023). Artificial Intelligence Automated Task Planning for Fabrication. In K. Dörfler, J. Knippers, A. Menges, S. Parascho, H. Pottmann, & T. Wortmann (Eds.), Advances in Architectural Geometry 2023 (pp. 249--260). De Gruyter. https://doi.org/doi:10.1515/9783111162683-019

  3. 2022

    1. Davidová, M., Fischer, L. K., & Teye, M. (2022). POL– AI: Leveraging Urban EcoSystem. In B. Sweeting (Ed.), Relating Systems Thinking and Design (RSD11) 2022 Symposium (pp. 1–11). Systemic Design Association.
    2. Akbar, Z., Wood, D., Kiesewetter, L., Menges, A., & Wortmann, T. (2022). A Data-Driven Workflow for Modelling Self-Shaping Wood Bilayer, Utilizing Natural Material Variations with Machine Vision and Machine Learning. In J. van Ameijde, N. Gardner, K. H. Hyun, L. Dan, & U. Sheth (Eds.), CAADRIA proceedings: Vol. Volume 1 (pp. 393–402). CAADRIA. https://doi.org/10.52842/conf.caadria.2022.1.393
    3. Elshani, D., Wortmann, T., & Staab, S. (2022, May). Towards Better Co-Design with Disciplinary Ontologies: Review and Evaluation of Data Interoperability in the AEC Industry. In Proceedings of LDAC2022 - 10th Linked Data in Architecture and Construction Workshop. LDAC2022 - 10th Linked Data in Architecture and Construction Workshop, Hersonissos, Greece.
    4. Elshani, D., Lombardi, A., Fisher, A., Staab, S., Hernández, D., & Wortmann, T. (2022, May). Knowledge Graphs for Multidisciplinary Co-Design: Introducing RDF to BHoM. In Proceedings of LDAC2022 - 10th Linked Data in Architecture and Construction Workshop. LDAC2022 - 10th Linked Data in Architecture and Construction Workshop, Hersonissos, Greece.
    5. Skoury, L., Amtsberg, F., Yang, X., Wagner, H. J., Menges, A., & Wortmann, T. (2022). A Framework for Managing Data in Multi-actor Fabrication Processes. In C. Gengnagel, O. Baverel, G. Betti, M. Popescu, M. R. Thomsen, & J. Wurm (Eds.), Towards Radical Regeneration (pp. 601–615). Springer International Publishing. https://doi.org/10.1007/978-3-031-13249-0_47
    6. Zorn, M., Catunda, N., Claus, L., Kobylinska, N., Frey, M., & Wortmann, T. (2022). Replacing energy simulations with surrogate models for design space exploration. Bauphysik, 44(6), Article 6. https://doi.org/10.1002/bapi.202200034
    7. Sherkat, Shermin., Wortmann, Andreas., & Wortmann, Thomas. (2022). Potentials of Symbolic AI Planning for Construction. Forumbauinformatik. https://www.researchgate.net/publication/363481115_Potentials_of_Symbolic_AI_Planning_for_Construction
    8. Zorn, M., Catunda, N., Claus, L., Kobylinska, N., Frey, M., & Wortmann, T. (2022, September 22). Replacing Time-Consuming Building Performance Simulations with Real-Time Surrogate Models and their Application in Early-Stage Design Space Exploration. Proceedings of BauSim Conference 2022. BauSIM 2022, Bauhaus-Universität Weimar. https://publications.ibpsa.org/conference/?id=bausim2022
    9. Wortmann, T., Cichocka, J., & Waibel, C. (2022). Simulation-based Optimization in Architecture and Building Engineering—Results from an International User Survey in Practice and Research. Energy and Buildings, 259, Article 259. https://doi.org/10.1016/j.enbuild.2022.111863
    10. Elshani, D., Lombardi, A., Fisher, A., Staab, S., Hernández, D., & Wortmann, T. (2022, September). Inferential Reasoning in Co-Design Using Semantic Web Standards alongside BHoM. Proceedings of 33. Forum Bauinformatik. https://doi.org/10.14459/2022md1686600

  4. 2021

    1. Natanian, J., & Wortmann, T. (2021). Simplified evaluation metrics for generative energy-driven urban design: A morphological study of residential blocks in Tel Aviv. Energy and Buildings, 240, 110916. https://linkinghub.elsevier.com/retrieve/pii/S0378778821002000
    2. Wortmann, T., & Natanian, J. (2021). Optimizing solar access and density in Tel Aviv: Benchmarking multi-objective optimization algorithms. Journal of Physics: Conference Series, 2042(1), Article 1. https://doi.org/10.1088/1742-6596/2042/1/012066
    3. Natanian, J., Luca, F. D., Wortmann, T., & Capeluto, G. (2021). The Solar Block Generator: an additive parametric method for solar driven urban block design. Journal of Physics: Conference Series, 2042(1), Article 1. https://doi.org/10.1088/1742-6596/2042/1/012049
    4. Petrov, M., & Wortmann, T. (2021, April). Latent fitness landscapes - Exploring performance within the latent space of post-optimization results. Proceedings of the Symposium on Simulation for Architecture & Urban Design.
    5. Waibel, C., Zhang, R., & Wortmann, T. (2021, April). Physics Meets Machine Learning: Coupling FFD with Regression Models for Wind Pressure Prediction on High-Rise Facades. Proceedings of the Symposium on Simulation for Architecture & Urban Design.

Contact Information

This image shows Thomas Wortmann

Thomas Wortmann

Tenure-Track prof. Dr.

Tenure-Track Professor

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