Welcome
I am an AI Researcher and Electrical Engineer, with academic and industrial experience across diverse technology sectors.
Academic CV
- Since 2024: Postdoctoral Researcher, Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany
- 2024: Doctor of Theoretical Medicine (Dr. rer. medic.), RWTH Aachen University, Aachen, Germany, GPA: 1.0/1.0 (magna cum laude)
- 2021: M.Sc. Thesis in Medical Image and Data Processing, Harvard Medical School, Boston, MA, USA, Grade: 100%
- 2021: M.Sc. in Electrical Engineering - Signal Processing & Communications, FAU, Erlangen, Germany, GPA: 92%, magna cum laude
- 2017: B.Sc. in Electrical Engineering, Bu-Ali Sina University, Iran, GPA: 86%
- 2013: High-School Diploma in Mathematics & Physics, National Organization for Development of Exceptional Talents, Iran, GPA: 94%
Key Competencies
- Deep Learning
- Medical Image Analysis
- Computer Vision
- Privacy-Preserving AI
- Generative AI
- Natural & Spoken Language Processing
- Research & Development
News
Click here to see the older news!
July 24, 2024: Editorial comment on our Radiology article by RSNA is available online [Click here]
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"Intraindividual Comparison of Different Methods for Automated BPE Assessment at Breast MRI: A Call for Standardization"
By: G. Müller-Franzes, F. Khader, S. Tayebi Arasteh, et al. in Radiology
June 15, 2024: Happy to announce that I received the June 2024 issue of the Paper of the Month award from the RWTH Aachen University for the paper on streamlining clinical studies with LLMs.
May 10, 2024:
I had the opportunity to present 2 abstracts at the 105. Deutschen Röntgenkongress (105th German X-ray congress) in Wiesbaden, Germany:
Feb 21, 2024: My paper on streamlining clinical studies with LLMs is now published by Nature Communications!
By: S. Tayebi Arasteh, et al. in Nature Communications
By: S. Tayebi Arasteh, et al. in Nature Communications
Feb 8, 2024: Celebrating 200 citations on Google Scholar🥳
Jan 17, 2024: Editorial comment on my Radiology AI article by RSNA is available online [Click here]
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"Securing Collaborative Medical AI by Using Differential Privacy: Domain Transfer for Classification of Chest Radiographs"
By: S. Tayebi Arasteh, et al. in Radiology: Artificial Intelligence
Dec 16, 2023: Final version of the open-source article is now published! [Click here]
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"Encrypted federated learning for secure decentralized collaboration in cancer image analysis"
By: D. Truhn*, S. Tayebi Arasteh*, et al. in Medical Image Analysis
March 21, 2023: Editorial comment on our Radiology article by RSNA is available online [Click here]
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"Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images"
By: G. Müller-Franzes, L. Huck, S. Tayebi Arasteh, et al. in Radiology
Featured Publications
Click here for the full list of publications!
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S. Tayebi Arasteh, T. Han, M. Lotfinia, C. Kuhl, J.N. Kather, D. Truhn, S. Nebelung. "Large language models streamline automated machine learning for clinical studies". Nature Communications (2024), 15(1), 1603. Nature Portfolio, DOI: 10.1038/s41467-024-45879-8
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S. Tayebi Arasteh, A. Ziller, C. Kuhl, M. Makowski, S. Nebelung, R. Braren, D. Rueckert, D. Truhn, G. Kaissis. "Preserving fairness and diagnostic accuracy in private large-scale AI models for medical imaging". Communications Medicine (2024), 4(1), 46. Nature Portfolio, DOI: 10.1038/s43856-024-00462-6
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S. Tayebi Arasteh, T. Arias-Vergara, P.A. Perez-Toro, T. Weise, K. Packhäuser, M. Schuster, E. Noeth, A. Maier, S.H. Yang. "Addressing challenges in speaker anonymization to maintain utility while ensuring privacy of pathological speech." Communications Medicine (2024), 4, 182, Nature Portfolio, DOI: 10.1038/s43856-024-00609-5
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S. Tayebi Arasteh, M. Lotfinia, T. Nolte, M.J. Sähn, P. Isfort, C. Kuhl, S. Nebelung, G. Kaissis, D. Truhn. "Securing Collaborative Medical AI by Using Differential Privacy: Domain Transfer for Classification of Chest Radiographs". Radiology: Artificial Intelligence (2024), 6(1), e230212. RSNA, DOI: 10.1148/ryai.230212
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D. Truhn*, S. Tayebi Arasteh* et al. "Encrypted federated learning for secure decentralized collaboration in cancer image analysis". Medical Image Analysis (2024), 92, 103059. DOI: 10.1016/j.media.2023.103059
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S. Tayebi Arasteh, C. Kuhl, M.J. Saehn, P. Isfort, D. Truhn, S. Nebelung. "Enhancing domain generalization in the AI-based analysis of chest radiographs with federated learning". Scientific Reports (2023), 13(1), 22576. Nature Portfolio, DOI: 10.1038/s41598-023-49956-8
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S. Tayebi Arasteh, P. Isfort, M. Saehn, G. Mueller-Franzes, F. Khader, J.K. Kather, C. Kuhl, S. Nebelung, D. Truhn. "Collaborative training of medical artificial intelligence models with non-uniform labels". Scientific Reports (2023), 13(1), 6046. Nature Portfolio, DOI: 10.1038/s41598-023-33303-y
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S. Tayebi Arasteh, J. Romanowicz, D.F. Pace, P. Golland, A.J. Powell, A.K. Maier, D. Truhn, T. Brosch, J. Weese, M. Lotfinia, R.J. van der Geest, M.H. Moghari. "Automated segmentation of 3D cine cardiovascular magnetic resonance imaging". Frontiers in Cardiovascular Medicine (2023), 10. DOI: 10.3389/fcvm.2023.1167500
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S. Tayebi Arasteh, T. Weise, M. Schuster, E. Noeth, A.K. Maier, S.H. Yang. "The effect of speech pathology on automatic speaker verification: a large-scale study". Scientific Reports (2023), 13(1), 20476. Nature Portfolio, DOI: 10.1038/s41598-023-47711-7
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G. Müller-Franzes, F. Khader, S. Tayebi Arasteh, L. Huck, M. Bode, T. Han, T. Lemainque, J.N. Kather, S. Nebelung, C. Kuhl, D. Truhn. "Intraindividual Comparison of Different Methods for Automated BPE Assessment at Breast MRI: A Call for Standardization." Radiology (2024), 3012(1), e232304. RSNA, DOI: 10.1148/radiol.232304
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F. Khader, G. Müller-Franzes, S. Tayebi Arasteh, T. Han, C. Haarburger, M. Schulze-Hagen, P. Schad, S. Engelhardt, B. Baeßler, S. Foersch, J. Stegmaier, C. Kuhl, S. Nebelung, J.N. Kather, D. Truhn. "Denoising diffusion probabilistic models for 3D medical image generation". Scientific Reports (2023), 13(1), 7303. Nature Portfolio, DOI: 10.1038/s41598-023-34341-2
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F. Khader, G. Müller-Franzes, T. Wang, T. Han, S. Tayebi Arasteh, C. Haarburger, J. Stegmaier, K. Bressem, C. Kuhl, S. Nebelung, J.N. Kather, D. Truhn. "Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for Transformers". Radiology (2023), 309(1), e230806. RSNA, DOI: 10.1148/radiol.230806
- G. Müller-Franzes, L. Huck, S. Tayebi Arasteh, F. Khader, T. Han, V. Schulz, E. Dethlefsen, J.N. Kather, S. Nebelung, T. Nolte, C. Kuhl, D. Truhn. "Using Machine Learning to Reduce the Need for Contrast Agents in Breast MRI through Synthetic Images". Radiology (2023), 307(3), e222211. RSNA, DOI: 10.1148/radiol.222211
PEER-REVIEWER ROLES
Click here for the full list of journals!
- Nature Portfolio:
- Eurosurveillance
- IEEE:
- Elsevier:
- SpringerOpen:
- PLOS:
- JMIR Publications:
- Frontiers:
- IET:
- Other publishers: