Dr. Ahmed Abdulkadir

Work at ZHAW

Position

Scientist, expert, innovator, reviewer, mentor

Professional development teaching

CAS Advanced Machine Learning and Machine Learning Operations

Education and Continuing education

Expertise and research interests

Machine learning, deep learning, medical image analysis, industrial AI

Experience

Automation engineer
Kowap AG
01 / 2008 - 07 / 2012

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

Projects

• Master3D – 3D-Master for a Digitized Manufacturing Platform / Team member / Project ongoing
• DISTRAL: Industrial Process Monitoring for Injection Molding with Distributed Transfer Learning / Team member / Project ongoing

Publications

• Rathore, Saima; Iftikhar, Muhammad A.; Chaddad, Ahmad; Singh, Ashish; Gillani, Zeeshan; Abdulkadir, Ahmed,

  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).

  Available from: https://doi.org/10.1016/j.cmpb.2023.107812

• Abdulkadir, Ahmed; Bathula, Deepti R.; Dvornek, Nicha C.; Govindarajan, Sindhuja T.; Habes, Mohamad; Kumar, Vinod; Leonardsen, Esten; Wolfers, Thomas; Xiao, Yiming, 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.

  Lecture Notes in Computer Science ; 14312.

  ISBN 978-3-031-44857-7.

  Available from: https://doi.org/10.1007/978-3-031-44858-4

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.

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