Dr. Lukas Lichtensteiger

Projects

• Blockchain-Enabled Financing of Supply Chains / Project leader / ongoing
• Blockchain-Enabled Sustainable Financing / Project leader / completed
• Blockchain-Based Verified Career Records for Enhanced Professional Credibility / Team member / completed
• Agroforestry Carbon Token System / Team member / completed
• SpaceVote / Project leader / completed
• Neurological ICU Data / Team member / completed
• AI powered CBCT for improved Combination Cancer Therapy / Deputy project leader / completed
• Decentralized financing of Fairtrade producers using a blockchain-based solution / Team member / completed
• DIR3CT: Deep Image Reconstruction through X-Ray Projection-based 3D Learning of Computed Tomography Volumes / Team member / completed
• Data Driven Medical muscle Training / Deputy project leader / completed
• Libra: A One-Tool Solution for MLD4 Compliance / Team member / completed
• Complexity 4.0 / Team member / completed
• New sensor and actuator technologies for robots / Project leader / completed

Publications

Articles in scientific journal, peer-reviewed

• Barco, D., Stadelmann, M., Oswald, M., Herzig, I., Lichtensteiger, L., Paysan, P., Peterlik, I., Walczak, M., Menze, B., & Schilling, F.-P. (2026). MInDI-3D : iterative deep learning in 3D for sparse-view cone beam computed tomography. IEEE Access, 14, 6438–6449. https://doi.org/10.1109/access.2026.3652627
• Amirian, M., Montoya-Zegarra, J. A., Herzig, I., Eggenberger Hotz, P., Lichtensteiger, L., Morf, M., Züst, A., Paysan, P., Peterlik, I., Scheib, S., Füchslin, R. M., Stadelmann, T., & Schilling, F.-P. (2023). Mitigation of motion-induced artifacts in cone beam computed tomography using deep convolutional neural networks. Medical Physics, 50(10), 6228–6242. https://doi.org/10.1002/mp.16405
• Füchslin, R. M., Dumont, E., Flumini, D., Fuchs, H. U., Hauser, H., Jaeger, C., Scheidegger, S., Schönenberger-Deuel, J., Lichtensteiger, L., Luchsinger, R. H., & Weyland, M. (2014). Morphological control : a design principle for applications in space science. Journal of the British Interplanetary Society, 67, 305–313. http://adsabs.harvard.edu/abs/2014JBIS...67..305F

Book chapters, peer-reviewed

Hollenstein, L., Lichtensteiger, L., Stadelmann, T., Amirian, M., Budde, L., Meierhofer, J., Füchslin, R. M., & Friedli, T. (2019). Unsupervised learning and simulation for complexity management in business operations. In M. Braschler, T. Stadelmann, & K. Stockinger (Eds.), Applied data science : lessons learned for the data-driven business (pp. 313–331). Springer. https://doi.org/10.1007/978-3-030-11821-1_17

Written conference contributions, peer-reviewed

Herzig, I., Paysan, P., Scheib, S., Züst, A., Schilling, F.-P., Montoya, J., Amirian, M., Stadelmann, T., Eggenberger Hotz, P., Füchslin, R. M., & Lichtensteiger, L. (2022). Deep learning-based simultaneous multi-phase deformable image registration of sparse 4D-CBCT [Conference poster]. Medical Physics, 49(6), e325–e326. https://doi.org/10.1002/mp.15769

Other publications

• Barco, D., Stadelmann, M., Oswald, M., Herzig, I., Lichtensteiger, L., Paysan, P., Peterlik, I., Walczak, M., Menze, B., & Schilling, F.-P. (2025). MInDI-3D : iterative deep learning in 3D for sparse-view cone beam computed tomography. arXiv. https://doi.org/10.48550/arXiv.2508.09616
• Lichtensteiger, L., Flumini, D., Gisler, L., Molnár, V., & Schaefer, M. (2023, January 11). Space vote : make your presence count. Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023. https://doi.org/10.21256/zhaw-27412
• Flumini, D., & Lichtensteiger, L. (2023, January 11). Decentralized financing of Fairtrade producers using a blockchain-based solution. Datalab Symposium, Winterthur, Schweiz, 11. Januar 2023. https://doi.org/10.21256/zhaw-27494

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