Dr. Ehsan Ullah | Hamad Bin Khalifa University
Hamad Bin Khalifa University


Dr. Ehsan Ullah

Dr. Ehsan Ullah

Post-Doctoral Researcher
Qatar Center for Artificial Intelligence
Qatar Computing Research Institute

  • Phone+974 44545737
  • Office locationOffice Number A102, 1st Floor, Research and Development Complex


Dr. Ehsan Ullah is a post-doctoral researcher at Qatar Computing Research Institute, Hamad Bin Khalifa University. Dr. Ullah received his Ph.D. degree in 2014 from Tufts University, Medford, Massachusetts. He received his M.Sc. and B.Sc. from University of Engineering and Technology, Lahore. Ehsan Ullah is interested in health informatics, computational biology, genomics and algorithms.

Research Interests

  • Health informatics
  • Computational biology
  • Genomics and algorithms.


Research / Teaching Assistant

Tufts University, Medford, USA.

  • Lecturer

    Department of Electrical Engineering, University of Engineering and Technology Pakistan.

  • Research Assistant/Associate

    Al-Khwarizmi Institute of Computer Science, Lahore Pakistan



Ph.D. Computer Science

Tufts University Medford, USA

  • M.Sc

    Electrical Engineering University of Engineering and Technology Lahore, Pakistan

  • B.Sc.

    Electrical Engineering University of Engineering and Technology Lahore, Pakistan


Selected Publications

  • N Hassanpour, E Ullah, M Yousofshahi, NU Nair, S Hassoun;

    Selection Finder (SelFi): A computational metabolic engineering tool to enable directed evolution of enzymes; Metabolic Engineering Communications 4, 37-47

  • M Aupetit, E Ullah, R Rawi, H Bensmail;

    A design study to identify inconsistencies in kinship information: The case of the 1000 Genomes project; Pacific Visualization Symposium (PacificVis), 2016 IEEE, 254-258

  • E Ullah, S Aeron, S Hassoun; gEFM

    An algorithm for computing elementary flux modes using graph traversal; IEEE/ACM Transactions on Computational Biology and Bioinformatics

  • E Ullah, M Walker, K Lee, S Hassoun; PreProPath

    An uncertainty-aware algorithm for identifying predictable profitable pathways in biochemical networks; IEEE/ACM transactions on computational biology and bioinformatics

  • GV Sridharan, E Ullah, S Hassoun, K Lee;

    Discovery of substrate cycles in large scale metabolic networks using hierarchical modularity; BMC systems biology 9 (1)

  • E Ullah, M Shahzad, R Rawi, M Dehbi, K Suhre, M Selim, D Mook, H Bensmail;

    Integrative 1H-NMR-based metabolomic profiling to identify type-2 diabetes biomarkers: An application to a population of Qatar; Metabolomics 5 (1),