Sumeer Khan, PhD

Postdoctoral Fellows


Research Interests

Dr. Khan's research interest spans from supervised and unsupervised deep learning in the medical image domain to the computational biology. He primary focuses on the automatic generation of new knowledge from the biological data through Machine Learning and to gain an understanding of the relationships between the biological systems and their molecular properties. This understanding is of fundamental importance in personalized medicine.

Selected Publications

  • Ensemble classification with modified SIFT descriptor for medical image modality. Khan, S.A., Yong, S. P., & Deng, J. D. (2016, December). In Image and Vision Computing New Zealand (IVCNZ), International Conference on (pp. 1-6). 2015
  • An Evaluation of Convolutional Neural Nets for Medical Image Anatomy Classification. Khan, S. A., & Yong, S. P. In Advances in Machine Learning and Signal Processing (pp. 293-303). Springer International Publishing, 2016
  • Modality Classification of Medical Images with Distributed Representations Based on Cellular Automata Reservoir Computing. Kleyko, Denis, Sumeer Khan, Evgeny Osipov, and Yong, S. P. In IEEE International Symposium on Biomedical Imaging. 2017
  • A deep learning architecture for classifying medical images of anatomy object. Khan, S., & Yong, S. P. In Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC), 2017 (pp. 1661-1668)
  • A comparison of deep learning and handcrafted features in medical image modality classification. Khan, S., & Yong, S. P. In Computer and Information Sciences (ICCOINS), 2016 3rd International Conference on (pp. 633-638)



  • Ph.D., Computer Science. Universiti Teknologi PETRONAS Malaysia

Professional Profile

  • 2019-Present: Postdoctoral fellow, KAUST, Thuwal,Saudi Arabia
  • 2014-2018 : Graduate research assistant, Universiti Teknologi PETRONAS Malaysia


  • Erasmus+Outside European Mobility Program GA,
  • Universiti Teknologi PETRONAS Graduate Scholarship Category A

KAUST Affiliations

  • ​KAUST Environmental Epigenetics Program (KEEP)
  • Biological and Environmental Sciences and Engineering (BESE)

Research Interests Keywords

Machine learning Unsupervised deep learning Single cell analysis Medical Image analysis

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