Dr. Ahmed Abdulkadir

Work at ZHAW

Position

Scientist, expert, innovator, reviewer, mentor

Focus

• Machine learning
• Deep learning
• Medical image analysis
• Industrial AI

Teaching

• AI in Medicine
• Computer Vision with Deep Learning
• Introduction to Artificial Intelligence
• Guest lecture Introduction to AI for BSc in Ergotherapy

Professional development teaching

CAS Advanced Machine Learning and Machine Learning Operations

Experience

• Expert Data Analyst (part-time)
  University Hospital of Old Age Psychiatry and Psychotherapy
  08 / 2023 - today
• Senior Researcher
  ZHAW
  03 / 2023 - today
• Senior Researcher
  Centre hospitalier universitaire vaudois (CHUV)
  02 / 2022 - 02 / 2023
• Research Fellow / Visiting Researcher
  University of Pennsylvania
  08 / 2019 - 01 / 2022
• Researcher
  University Hospital of Old Age Psychiatry and Psychotherapy
  01 / 2019 - 01 / 2020
• Research Assistant / PhD Student
  University Hospital of Old Age Psychiatry and Psychotherapy
  11 / 2016 - 12 / 2018
• Research Assistant / PhD Student
  University Medical Center Freiburg-im-Breisgau
  08 / 2012 - 10 / 2016
• Automation engineer
  Kowap AG
  01 / 2008 - 07 / 2012

Education and Continuing education

Education

• PhD / Computer sciences
  Albert-Ludwigs-University Freiburg-im-Breisgau
  08 / 2012 - 12 / 2018
• MSc / Life sciences
  École Polytechnique Fédérale de Lausanne
  09 / 2010 - 07 / 2012
• BSc / Life sciences
  École Polytechnique Fédérale de Lausanne
  09 / 2007 - 07 / 2010
• BSc / Systems engineering
  NTB Buchs
  09 / 2001 - 08 / 2004

Network

Membership of networks

/ ORCID: 0000-0003-4679-8081

ORCID digital identifier

ORCID ID: 0000-0003-4679-8081

Projects

• Automated Music Track Extraction and Identification from Full-Length Movies / Project leader / ongoing
• dAIrector – Automated multi-camera live production for events / Team member / ongoing
• Evidence-Based Diagnostic Assistance for Echocardiography / Project leader / ongoing
• Study on semi-automatic poster cataloguing at the Swiss National Library / Team member / completed
• 3D-Master for a Digitized Manufacturing Platform / Team member / completed
• DISTRAL: Industrial Process Monitoring for Injection Molding with Distributed Transfer Learning / Team member / completed

Publications

Articles in scientific journal, peer-reviewed

• Meyer, B. et al. (2026) 'A document is worth a structured record : principled inductive bias design for document recognition', International Journal on Document Analysis and Recognition. doi: 10.1007/s10032-026-00602-9.
• Sager, P. J. et al. (2026) 'A comprehensive survey of agents for computer use : foundations, challenges, and future directions', Journal of Artificial Intelligence Research, 85(34). doi: 10.1613/jair.1.19490.
• Henzen, N. A. et al. (2025) 'Automated segmentation for cortical thickness of the medial perirhinal cortex', Scientific Reports, 15(14903). doi: 10.1038/s41598-025-98399-w.
• Govindarajan, S. T. et al. (2025) 'Machine learning reveals distinct neuroanatomical signatures of cardiovascular and metabolic diseases in cognitively unimpaired individuals', Nature Communications, 16(1), p. 2724. doi: 10.1038/s41467-025-57867-7.
• Jermain, P. R. et al. (2024) 'Deep learning-based cell segmentation for rapid optical cytopathology of thyroid cancer', Scientific Reports, 14(1), p. 16389. doi: 10.1038/s41598-024-64855-2.
• Yan, P. et al. (2024) 'A comprehensive survey of deep transfer learning for anomaly detection in industrial time series : methods, applications, and directions', IEEE Access, 12, pp. 3768–3789. doi: 10.1109/ACCESS.2023.3349132.
• Rathore, S. et al. (2023) 'Imaging phenotypes predict overall survival in glioma more accurate than basic demographic and cell mutation profiles', Computer Methods and Programs in Biomedicine, 242(107812). doi: 10.1016/j.cmpb.2023.107812.

Written conference contributions, peer-reviewed

• Ali, W. et al. (2026) 'Automated component testing for agentic AI in medical decision support systems', in 12th IAPR TC3 Workshop on Artificial Neural Networks for Pattern Recognition (ANNPR), Milan, Italy, 7-9 October 2026. ZHAW Zurich University of Applied Sciences. doi: 10.21256/zhaw-37093.
• Lack, S. et al. (2026) 'A unified cost estimation framework combining milling, turning, AM, and sheet metal processing', in IFIP 23rd International Conference on Product Lifecycle Management, Lecce, Italy, 6-8 July 2026. ZHAW Zurich University of Applied Sciences. doi: 10.21256/zhaw-37255.
• Ali, W. et al. (2026) 'Automated, vendor-agnostic measurement of myocardial tissue velocities in echocardiography', in 2026 IEEE 23rd International Symposium on Biomedical Imaging (ISBI). IEEE. doi: 10.1109/isbi61048.2026.11515716.
• Meyer, B. et al. (2025) 'Hounsfield unit ranges as inductive bias for intra-clinical learning of data-efficient CT segmentation models', in 2025 IEEE Swiss Conference on Data Science (SDS). IEEE, pp. 1–7. doi: 10.1109/SDS66131.2025.00008.
• Yan, P. et al. (2025) 'Learning actionable world models for industrial process control', in 2025 IEEE Swiss Conference on Data Science (SDS). IEEE, pp. 111–118. doi: 10.1109/SDS66131.2025.00022.
• Lanfant, B. et al. (2025) '3D-master-based method for optimizing the cost calculation of PBF-LB/M manufactured parts', in BHM Berg- und Hüttenmännische Monatshefte. Springer, pp. 158–171. doi: 10.1007/s00501-025-01563-y.
• Yan, P. et al. (2024) 'Automated process monitoring in injection molding via representation learning and setpoint regression', in 2024 11th IEEE Swiss Conference on Data Science (SDS). IEEE, pp. 138–145. doi: 10.1109/SDS60720.2024.00027.
• Jermain, P. R. et al. (2024) 'Rapid optical cytology with deep learning-based cell segmentation for diagnosis of thyroid lesions', in Optica Biophotonics Congress: Biomedical Optics 2024 (Translational, Microscopy, OCT, OTS, BRAIN). Optica Publishing Group, p. MTu4A.5. doi: 10.1364/MICROSCOPY.2024.MTu4A.5.
• Abdulkadir, A. et al. (eds) (2023) Machine learning in clinical neuroimaging, 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN), held in conjunction with MICCAI 2023, Vancouver, Canada, 8-12 October 2023. Cham: Springer. doi: 10.1007/978-3-031-44858-4.

Oral conference contributions and abstracts

Lanfant, B. et al. (2024) '3D-master-based method for optimizing the cost calculation of PBF-LB/M manufactured parts', in Metal Additive Manufacturing Conference (MAMC), Aachen, Germany, 17-19 September 2024.

Publications before appointment at the ZHAW

• Chaddad, A.; Lu, Q.; Li, J.; Katib, Y.; Kateb, R.; Tanougast, C.; Bouridane, A.; Abdulkadir, A. (2023) Explainable, Domain-Adaptive, and Federated Artificial Intelligence in Medicine. IEEE/CAA J. Autom. Sinica 10, 859–876.
• Yang, Z.; Nasrallah I.M.; Shou, H.; Wen, J.; Doshi, J.; Habes, M.; Erus, G.; Abdulkadir, A.; Resnick, S.M.; Albert, M.S.; Maruff, P.; Fripp, J.; Morris, J.C.; Wolk, D.A.; Davatzikos, C. (2021) A deep learning framework identifies dimensional representations of Alzheimer's Disease from brain structure. Nat Commun 12, 7065.
• Anastasopoulos, C., Yang, S., Pradella, M., Akinci D'Antonoli, T., Knecht, S., Cyriac, J., Reisert, M., Kellner, E.; Achermann, R.; Haaf, P.; Stieltjes, B.; Sauter, A.W.; Bremerich, J.; Sommer, G.; Abdulkadir, A. (2021) Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium. J Cardiovasc Magn Reson 23, 133.
• Rathore, S.; Abdulkadir, A.; Davatzikos, C. (2020) Analysis of MRI Data in Diagnostic Neuroradiology. Annu. Rev. Biomed. Data Sci. 3, 365–390.
• Çiçek, Ö; Abdulkadir, A; Lienkamp, SS; Brox, T; Ronneberger, O. 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation, International Conference on Medical Image Computing and Computer-Assisted Intervention (2016)
• Google Scholar Publication List

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