Projects per year
Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being -
SDG 5 Gender Equality -
SDG 7 Affordable and Clean Energy -
SDG 8 Decent Work and Economic Growth -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 10 Reduced Inequalities -
SDG 11 Sustainable Cities and Communities -
SDG 13 Climate Action -
SDG 16 Peace, Justice and Strong Institutions
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Dive into the research topics where Felix Dietrich is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
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Projects
- 5 Active
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SAFEMAP: Structural Assessment and Optimization using Fast and Efficacious Multi-data AI Approaches with Hybrid Multi-Physics under Natural Hazards
Dietrich, F. (PI), Wüchner, R. (PI) & Li, V. M. (CoI)
1/11/25 → 28/02/30
Project: Research
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AutoMD-AI: Surrogatmodelle und Auto-Tuning-Verfahren für molekulare Fluidsimulation
Dietrich, F. (PI) & Neumann, P. (PI)
1/10/24 → 30/09/27
Project: Research
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Pedestrian dynamics prediction for safe and flow-efficient building design
Dietrich, F. (PI), Borrmann, A. (PI) & Čukarska, A. (CoI)
27/11/23 → 26/11/27
Project: Research
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Deep physics based structural health monitoring
Dietrich, F. (PI), Kollmannsberger, S. S. (PI), Bungartz, H.-J. (PI) & Sun, Q. (CoI)
13/03/23 → 12/03/27
Project: Research
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Harmonic Artificial Intelligence based on Linear Operators
Dietrich, F. (PI), Bolager, E. (CoI) & Burak, I. (CoI)
1/04/22 → 31/03/28
Project: Research
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A Shape Is Worth 512 Numbers: Spectral-domain Diffusion Modeling for 3D Shape Generation
Fan, J., Trigui, A., Bonfanti, A., Dietrich, F., Back, T. & Wang, H., 2026, 2026 IEEE Conference on Artificial Intelligence, CAI 2026. Institute of Electrical and Electronics Engineers Inc., p. 1628-1634 7 p. (2026 IEEE Conference on Artificial Intelligence, CAI 2026).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
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Embedding-Based Methods for Linear Solver Performance Prediction
Liu Weng, H., Bungartz, H. J. & Dietrich, F., 2026, Computational Science – ICCS 2026 - 26th International Conference, Proceedings. Neumann, P., Puma, M. J., Lees, M. H., Sloot, P. M. A., Groen, D. & Dongarra, J. J. (eds.). Springer Science and Business Media Deutschland GmbH, p. 472-486 15 p. (Lecture Notes in Computer Science; vol. 16783 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review
Open Access -
Graph neural networks for full waveform inversion
Singh, D. S., Herrmann, L., Bürchner, T., Dietrich, F. & Kollmannsberger, S., 2026, (Accepted/In press) In: Computational Mechanics.Research output: Contribution to journal › Article › peer-review
Open Access -
Machine learning in pedestrian and evacuation dynamics for the built environment: A systematic literature review
Berggold, P., Čukarska, A., Nousias, S., Dietrich, F. & Borrmann, A., Jun 2026, In: Safety Science. 198, 107143.Research output: Contribution to journal › Review article › peer-review
Open Access1 Scopus citations -
Machine learning in pedestrian and evacuation dynamics for the built environment: A systematic literature review
Berggold, P., Čukarska, A., Nousias, S., Dietrich, F. & Borrmann, A., 2026, In: Safety Science. 198, p. 107143 1 p.Research output: Contribution to journal › Article › peer-review