Soroosh Tayebi Arasteh
Dr.-Ing. Dr. rer. medic. Soroosh Tayebi Arasteh
Postdoctoral Researcher
Martensstr. 3
91058 Erlangen
Department of Computer Science
Chair of Computer Science 5 (Pattern Recognition)
Martensstr. 3
91058 Erlangen
- Phone number: +49 9131 85-27775
- Fax number: +49 9131 85-27270
- Email: soroosh.arasteh@fau.de
- Website: https://lme.tf.fau.de/person/arasteh/
Academic CV
- Since 2024: Postdoctoral Researcher at the Pattern Recognition Lab
- 2024: Doctor of Theoretical Medicine (Dr. rer. medic.), RWTH Aachen University, Aachen, Germany
- 2024: Doctor of Engineering (Dr.-Ing.) in Computer Science, FAU Erlangen-Nürnberg, Erlangen, Germany
- 2021: M.Sc. Thesis in Medical Image and Data Processing, Harvard Medical School, Boston, MA, USA
- 2021: M.Sc. in Communications and Multimedia Engineering, FAU Erlangen-Nürnberg, Erlangen, Germany
- 2017: B.Sc. in Electrical Engineering, Bu-Ali Sina University, Hamedan, Iran
Publications
Please visit my website for an up-to-date list of journals.
Selected Journal 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)
- 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)
- S. Tayebi Arasteh, T. Arias Vergara, P. Perez, 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)
- 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)
- 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)
- D. Truhn*, S. Tayebi Arasteh* (shared first author), et al. “Encrypted federated learning for secure decentralized collaboration in cancer image analysis“. Medical Image Analysis (2024)
- 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)
- S. Tayebi Arasteh, P. Isfort, M. Saehn, G. Mueller-Franzes, F. Khader, J.N. Kather, C. Kuhl, S. Nebelung, D. Truhn. “Collaborative training of medical artificial intelligence models with non-uniform labels.” Scientific Reports (2023)
- S. Tayebi Arasteh, T. Weise, M. Schuster, E. Nöth, A.K. Maier, S.H. Yang. “The effect of speech pathology on automatic speaker verification: a large-scale study.” Scientific Reports (2023)
- S. Tayebi Arasteh, L. Misera, J.N. Kather, D. Truhn, S. Nebelung. “Enhancing diagnostic deep learning via self-supervised pretraining on large-scale, unlabeled non-medical images.” European Radiology Experimental (2024)
- 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)
Current Journal Roles
Please visit my website for an up-to-date list of journals.
Talks
Please visit my website for an up-to-date list of talks.
Lectures
- Advanced Deep Learning (Winter Semester 2024-2025)