قدِّم طلبك الآن 
إحسان الله
باحث بعد الدكتوراه
البريد الإلكتروني
eullah@qf.org.qaالهاتف
+974 44545737موقع المكتب
مكتب رقم أ102، الطابق الأول، مجمع البحوث والتنمية
إحسان الله
باحث بعد الدكتوراه
المؤهلات العلمية
Ph.D. Computer Science
M.Sc
الكيان
معهد قطر لبحوث الحوسبة
السيرة الذاتية
Dr. Ehsan Ullah is post-doctoral researcher at Qatar Computing Research Institute, Hamad Bin Khalifa University. Dr. Ehsan 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),