Soroosh Tayebi Arasteh

Postdoctoral AI Researcher | Dr.-Ing. Dr. rer. medic.


Pattern Recognition Lab
Friedrich-Alexander-Universität Erlangen-Nürnberg
Martensstr. 3
91058 Erlangen, Bavaria, Germany


Department of Urology
Stanford University
Palo Alto, CA, USA
Homepage
Email: tayebi@stanford.edu

Welcome

Profile photo

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 Experience

  • Since 03/2025: Postdoctoral Scholar, Departments of Urology and Radiology, Stanford University, Palo Alto, CA, USA
  • Since 08/2024: Postdoctoral Researcher and Lecturer, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU), Erlangen, Germany

  • Studies

  • 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!
Communications Medicine

August 1, 2025: I've been appointed as an editorial board member of Communications Medicine!

Radiology: AI trainee EB

July 1, 2025: I've been appointed as a trainee editorial board of Radiology: Artificial Intelligence!

1,000 Google Scholar citations

May 26, 2025: Just crossed 1,000 citations on Google Scholar!

Huge thanks to everyone I've collaborated with and learned from along the way,
couldn’t have done it without you!
European Radiology Experimental

February 1, 2025: I've been appointed as an editorial board member of European Radiology Experimental!

Section Radiography
Reviewer of the Year

January 28, 2025: I received the 2024 Reviewer of the Year Award

from European Radiology Experimental
  • Official journal of the European Society of Radiology
  • Doctorate #2

    December 20, 2024: I officially obtained my doctorate #2 🥳

    Dr.-Ing. in Computer Science from FAU Erlangen-Nuremberg, Germany
    Clarivate Analytics logo

    November 20, 2024: I just submitted my 100th journal peer-review!

    See Web of Science for more!
    Stanford logo

    November 1, 2024: Thrilled to announce that I will be joining Stanford Medicine as a postdoc!

    First doctoral degree

    July 31, 2024: I officially obtained my 1st doctoral degree 🥳

    Dr. rer. medic. in Theoretical Medicine from RWTH Aachen University, Germany
    Radiology journal

    July 24, 2024: Editorial comment on our Radiology article by RSNA is available online [Click here]

      "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

    Nature Communications

    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.

    Chest X-ray

    March 14, 2024: My journal papers 1, 2, 3, 4, and 5 on diagnostic deep learning using chest radiographs are published!



    Featured Publications

    Click here for the full list of publications!

      Nature Communications logo
      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
      Radiology AI logo
      S. Tayebi Arasteh, M. Lotfinia, K. Bressem, R. Siepmann, L. Adams, D. Ferber, C. Kuhl, J.N. Kather, S. Nebelung, D. Truhn. "RadioRAG: Online Retrieval-augmented Generation for Radiology Question Answering." Radiology: Artificial Intelligence (2025), RSNA
      Radiology logo
      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
      Communications Medicine logo
      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
      Radiology AI logo
      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
      Communications Medicine logo
      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
      Medical Image Analysis logo
      D. Truhn*, S. Tayebi Arasteh* et al. "Encrypted federated learning for secure decentralized collaboration in cancer image analysis". Medical Image Analysis (2024)
      Radiology logo
      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
      Radiology logo
      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
      Radiology logo
      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

    Communications Medicine European Radiology Experimental

    Trainee Editorial Board

    Radiology: Artificial Intelligence

    Peer-Reviewer

    As of August 16, 2025, my review service includes 198 reviews for a total of 68 different journals and 1 review for grants.

    Click here for the full list of reviews!

    Journals:

    Grants:

    • German Research Foundation (DFG)