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Dr. Halima Bensmail
Principal Scientist Joint Professor
Phone
+974 44540195Office location
1116, First Floor, HBKU Research Development Complex
Dr. Halima Bensmail
Principal Scientist Joint Professor
Educational Qualifications
PhD in Biostatistics
MSc in Statistical Machine Learning
Entity
Qatar Computing Research Institute
College of Science and Engineering
Divison
Qatar Center for Artificial Intelligence
Information & Computing Technology
Biography
Dr. Halima Bensmail is a Principal Scientist at the Qatar Computing Research Institute, a Professor at the College of Science and Engineering at Hamad Bin Khalifa University, and a visiting full Professor at Texas A&M University at Qatar. She received her PhD from Pierre & Marie Currie University in Paris, France, and worked as a postdoctoral fellow at the University of Washington and FHCRC in Seattle, Washington, USA. Halima was an assistant and associate professor at the University of Tennessee and the Virginia Medical School before joining Qatar Foundation. Halima's expertise lies in the frontiers of machine learning, bioinformatics, and computational biology, and she is also a statistician and a biostatistician.
She has published over 140 peer-reviewed papers in high-impact journals such as Nature Communications, Nucleic Acids Research, Genome Research, Briefings in Bioinformatics, Scientific Reports, and Bioinformatics. She has also earned multiple research awards taught courses in Qatar, the US, and France, and mentored many summer interns, and master's and PhD students. Halima has been the principal investigator and co-investigator on various research grants, and she is currently a member of a $2 million newly founded center provided by the USDA grant agency to the obesity center at Texas Tech. Halima has worked as a reviewer for the NIH and NSF, and she is a board member of the Artificial Intelligence and Quantum Technology Foundation in Davos and an AdCom representative of IEEE EMBs in MENA.
PhD in Biostatistics
Pierre and Marie Curie University, France
1996
MSc in Statistical Machine Learning
Pierre and Marie Curie University, France
1991
B.S. in Applied Mathematics and Statistics
University of Science - Rabat, Morocco
1989
- Machine learning and artificial intelligence for Multiomics and Multimodal data modeling
- Bioinformatics and computational biology and novel algorithms for biomarkers discovery and disease prediction and diagnosis
- Statistical inferences and their application in sciences
- Biostatistics and drug repurposing
Principal Scientist
Qatar Computing Research Institute, Hamad Bin Khalifa University
2011 - Present
Professor
College of Science and Engineering, Hamad Bin Khalifa University
2016 - Present
Associate Professor
Public Health, Eastern Virginia Medical School, United States
2006 - 2009
Associate Professor
Statistics, University of Tennessee, United States
2005 - 2006
Assistant Professor
Statistics, University of Tennessee, United States
2000 - 2005
Scientist
Data Theory, University of Leiden, Netherlands
1997 - 2000
Research Associate
Biostatistics, Fred Hutchinson Cancer Center, United States
1996 - 1997
Postdoc
Statistics, University of Washington, United States
1994 - 1996
Villiers, W., Mifsud, B., Lavender, P., Kelly, A., Bensmail, H., Elbasir, A., Dillon, A., & Osborne, C. (2023). Multi-omics and deep learning reveal context-specific gene regulatory activities of PML-RARA in acute promyelocytic leukemia. Nature Communications, 14(1), 724.
Patel, C. N., Mall, R., & Bensmail, H. (2023). AI-driven drug repurposing and binding pose meta-dynamics identifies novel targets for monkeypox virus. Journal of Infection and Public Health, 16(5), 799–807.
Chen, Z., Zhao, P., Li, F., Wang, Y., Smith, A. I., Webb, G. I., Akutsu, T., Baggag, A., Bensmail, H., & Song, J. (2020). DeepPRoMIse: A deep-learning framework for predicting two major types of RNA post-transcriptional modification sites from RNA sequences. Briefings in Bioinformatics, 21(5), 1676–1696.
Elbasir, A., Moovarkumudalvan, B., Kunji, K., Kolatkar, P., Mall, R., & Bensmail, H. (2020). A deep learning framework for sequence-based protein crystallization prediction. Journal of Bioinformatics, 35(13), 2216–2225.
Mall, R., Cerulo, L., Garofano, L., Frattini, V., Kunji, K., Bensmail, H., & Sabedot, T. S. (2020). RGBM: Regularized gradient boosting machines for identification of the transcriptional regulators of discrete glioma subtypes. Nucleic Acids Research, 46(7), e39.
- 2023; Research award for Women in AI awarded by “Middle East Enterprise AI & Analytics Summit.
- 2016; Best Contribution in Information Complexity awarded by the International Conference on Information Complexity and Statistical Modeling in High Dimensions with Applications (IC-SMHD-2016).
- 2013; Best Research Team of the 2013 NPRP outcome, awarded by Qatar National Research Fund, Doha, Qatar.
- 2011; Best Researcher in Computing, awarded by Annual Research Forum, Qatar Foundation.
- 2000; ONRST Postdoctoral Fellowship, Office of Naval Research Science and Technology, Arlington, Virginia, U.S.A.
- 1996; Best Research Award in Statistics for Classification, International Federation for Classification (IFCS96), Rome, Italy.
- 1994; Graduate Fellowship, Institute National for Research in Informatics and Automatics (INRIA), Versailles, France.