Dr. Ahmed Abdulkadir

Arbeit an der ZHAW

Tätigkeit

Wissenschaftler, Experte, Innovator, Gutachter, Mentor

Lehrtätigkeit in der Weiterbildung

CAS Advanced Machine Learning and Machine Learning Operations

Berufserfahrung

Automationsingenieur
Kowap AG
01 / 2008 - 07 / 2012

Aus- und Weiterbildung

Ausbildung

• Dr.-Ing. / Computerwissenschaften
  Albert-Ludwigs-Universität Freiburg
  08 / 2012 - 12 / 2018
• MSc / Sciences et technologies du vivant
  École Polytechnique Fédérale de Lausanne
  09 / 2010 - 07 / 2012
• BSc / Sciences et technologies du vivant
  École Polytechnique Fédérale de Lausanne
  09 / 2007 - 07 / 2010
• BSc / Systemtechnik
  NTB Buchs
  09 / 2001 - 08 / 2004

Projekte

• Master3D – 3D-Master for a Digitized Manufacturing Platform / Teammitglied / Projekt laufend
• DISTRAL: Industrial Process Monitoring for Injection Molding with Distributed Transfer Learning / Teammitglied / Projekt laufend

Publikationen

• Yan, Peng; Abdulkadir, Ahmed; Luley, Paul-Philipp; Rosenthal, Matthias; Schatte, Gerrit A.; Grewe, Benjamin F.; Stadelmann, Thilo,

  2024.

  A comprehensive survey of deep transfer learning for anomaly detection in industrial time series : methods, applications, and directions.

  IEEE Access.

  12, S. 3768-3789.

  Verfügbar unter: https://doi.org/10.1109/ACCESS.2023.3349132

• 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).

  Verfügbar unter: https://doi.org/10.1016/j.cmpb.2023.107812

• Yan, Peng; Abdulkadir, Ahmed; Aguzzi, Giulia; Schatte, Gerrit A.; Grewe, Benjamin F.; Stadelmann, Thilo,

  2024.

  Automated process monitoring in injection molding via representation learning and setpoint regression [Paper].

  In:

  11th IEEE Swiss Conference on Data Science (SDS), Zurich, Switzerland, 30-31 May 2024.

  ZHAW Zürcher Hochschule für Angewandte Wissenschaften.

  Verfügbar unter: https://doi.org/10.21256/zhaw-30430

• Jermain, Peter R.; Oswald, Martin; Langdun, Tenzin; Wright, Santana; Khan, Ashraf; Stadelmann, Thilo; Abdulkadir, Ahmed; Yaroslavsky, Ann N.,

  2024.

  Rapid optical cytology with deep learning-based cell segmentation for diagnosis of thyroid lesions [Paper].

  In:

  Proceedings of the 2024 Optica Biophotonics Congress: Biomedical Optics.

  Optica Biophotonics Congress: Biomedical Optics, Fort Lauderdale, USA, 7-10 April 2024.

  Optica Publishing Group.

  Verfügbar unter: https://doi.org/10.21256/zhaw-29674

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

  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.

  Verfügbar unter: https://doi.org/10.1007/978-3-031-44858-4

Publikationen vor Tätigkeit an der 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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