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Dr. Ehsan Ullah
Post-Doctoral Researcher
Phone
+974 44545737Office location
Office Number A102, 1st Floor, Research and Development Complex
Dr. Ehsan Ullah
Post-Doctoral Researcher
Educational Qualifications
Ph.D. Computer Science
M.Sc
Entity
Qatar Computing Research Institute
Divison
Qatar Center for Artificial Intelligence
Biography
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.
Ph.D. Computer Science
Tufts University Medford, USA
2014
M.Sc
Electrical Engineering University of Engineering and Technology Lahore, Pakistan
2007
B.Sc.
Electrical Engineering University of Engineering and Technology Lahore, Pakistan
2002
- Health informatics
- Computational biology
- Genomics and algorithms.
Research / Teaching Assistant
Tufts University, Medford, USA.
2008-2014
Lecturer
Department of Electrical Engineering, University of Engineering and Technology Pakistan.
2004-2008
Research Assistant/Associate
Al-Khwarizmi Institute of Computer Science, Lahore Pakistan
2003-2008
Selection Finder (SelFi): A computational metabolic engineering tool to enable directed evolution of enzymes; Metabolic Engineering Communications 4, 37-47
A design study to identify inconsistencies in kinship information: The case of the 1000 Genomes project; Pacific Visualization Symposium (PacificVis), 2016 IEEE, 254-258
An algorithm for computing elementary flux modes using graph traversal; IEEE/ACM Transactions on Computational Biology and Bioinformatics
An uncertainty-aware algorithm for identifying predictable profitable pathways in biochemical networks; IEEE/ACM transactions on computational biology and bioinformatics
Discovery of substrate cycles in large scale metabolic networks using hierarchical modularity; BMC systems biology 9 (1)
Integrative 1H-NMR-based metabolomic profiling to identify type-2 diabetes biomarkers: An application to a population of Qatar; Metabolomics 5 (1),