Welcome
I am an AI Scientist with a diverse background of two independent doctorates in engineering and medicine, with a strong focus on advancing research in deep learning. Through academic and applied roles in Germany and the USA, I bring expertise in deep learning across different data types including image, video, speech, text, and different medical imaging modalities, alongside experience leading research initiatives and mentoring junior researchers.
Academic CV
- Since 2024: Postdoctoral Researcher and Lecturer, 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: magna cum laude
- 2024: Doctor of Engineering (Dr.-Ing.) in Computer Science, FAU, Erlangen, Germany, GPA: 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 - Communications and Multimedia Engineering, 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
- Clinical Translational Research
News
Click here to see the older news!
January 28, 2025: I received the 2024 Reviewer of the Year Award
from European Radiology Experimental
December 20, 2024: I officially obtained my doctorate #2 🥳
Dr.-Ing. in Computer Science from FAU Erlangen-Nuremberg, Germany
November 20, 2024: I just submitted my 100th journal peer-review!
See Web of Science for more!
July 31, 2024: I officially obtained my 1st doctoral degree 🥳
Dr. rer. medic. in Theoretical Medicine from RWTH Aachen University, Germany
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
Featured Publications
Click here for the full list of publications!
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), Nature Portfolio
S. Tayebi Arasteh, R. Siepmann, M. Huppertz, M. Lotfinia, B. Puladi, C. Kuhl, D. Truhn, S. Nebelung. "The Treasure Trove Hidden in Plain Sight: The Utility of GPT-4 in Chest Radiograph Evaluation." Radiology (2024), RSNA
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), Nature Portfolio
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), RSNA
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), Nature Portfolio
D. Truhn*, S. Tayebi Arasteh* et al. "Encrypted federated learning for secure decentralized collaboration in cancer image analysis". Medical Image Analysis (2024)
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), RSNA
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), RSNA
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), RSNA
EDITORIAL SERVICE
Editorial Board Member
- European Radiology Experimental:
- Official journal of European Society of Radiology
- Section Computed Tomography | Since 02/2025
Peer-Reviewer
Click here for the full list of reviews!
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Nature Communications [IF: 14.7]
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npj Digital Medicine [IF: 12.4]
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Eurosurveillance [IF: 10.0]
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Medical Image Analysis [IF: 10.7]
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IEEE Transactions on Medical Imaging [IF: 8.9]
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View [IF: 9.7]
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npj Precision Oncology [IF: 6.8]
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Respirology [IF: 6.6]
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IEEE Journal of Biomedical and Health Informatics [IF: 6.7]
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Archives of Computational Methods in Engineering [IF: 9.7]
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Scientific Data [IF: 5.8]
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Scientific Reports [IF: 3.8]
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BMC Medicine [IF: 7.1]
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Journal of Medical Internet Research [IF: 5.8]
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Computerized Medical Imaging and Graphics [IF: 5.4]