Welcome
I am an AI Researcher and Network Engineer, with academic and industrial experience across diverse technology sectors. As a multidisciplinary software developer deeply passionate about emerging technologies and AI, I thrive on exploring the frontiers of innovation. With a keen interest in leveraging new materials and AI-driven solutions, I am dedicated to pushing boundaries and fostering advancements that drive positive change.
Experience & Education
Practical Experience
- 07/2024 - Present: Cloud Network Engineer, GOSP - Generali Operations Service Platform, Aachen, Germany
- 08/2022 - 06/2024: Research Employee - Mechanical Engineering, RWTH Aachen University, Aachen, Germany
- 02/2022 - 07/2022: Working Student - Data Science, WBA Aachener Werkzeugbau Akademie GmbH, Aachen, Germany
- 09/2021 - 01/2022: Working Student - Deep Learning, Virtonomy GmbH, Munich, Germany
Academic CV
- 09/2023 - 06/2024: Research Internship at the Lab for Artificial Intelligence in Medicine, University Hospital RWTH Aachen, Aachen, Germany
- 08/2022 - 06/2024: Ph.D. Student in Mechanical Engineering, RWTH Aachen University, Aachen, Germany (not completed)
- 04/2021 - 07/2022: Visiting Student in Computational Science, University of Regensburg, Regensburg, Germany
- 09/2018 - 07/2020: M.Sc. in Materials Science & Engineering, Sharif University of Technology
- 09/2014 - 07/2018: B.Sc. in Materials Science & Engineering, Bu-Ali Sina University, Iran
News
Click here to see the older news!
Feb 1, 2025: Celebrating 80 citations on Google Scholar🥳
Jan 28, 2025: Awarded as a reviewer of the Year 2024 by European Radiology Experimental!
Feb 21, 2024: Our paper on streamlining clinical studies with LLMs is now published by Nature Communications!
Jan 17, 2024: Editorial comment on our 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"
In Radiology: Artificial Intelligence
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), 15(1), 1603. Springer Nature, DOI: 10.1038/s41467-024-45879-8
- 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), 313(2), e233441. RSNA, DOI: 10.1148/radiol.233441
- 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
- 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
Voluntary Editorial Services
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Editorial Board Member
- European Radiology Experimental
Section Computed Tomography | Since February 2025
Peer-Reviewer
- Scientific Reports Nature Portfolio(2 papers; Since 2025)
- Journal of Medical Internet Research (JMIR), JMIR Publications (4 papers; Since 2024)
- JMIR AI, JMIR Publications (3 papers; Since 2024)
Contact
Feel free to reach out to me via contact form below.