Dr. Halima Bensmail

Principal Scientist
Data Analytics
+(974) 4454 0195
Leadership is the most important factor that attracted me to QCRI. Need for creativity is the second factor. Innovation is a very important factor at QCRI. At QCRI we are being challenged continuously, we have been asked to think big. We are supposed to do research with applications that are of great impact, nationally and internationally.

Research Focus at QCRI

Dr. Halima Bensmail is working broadly on statistical machine learning, applied it to medical areas for research that is referred to as: machine learning in Bioinformatics.

Her research focus includes:

  • Modelling -omics data (genomics, proteomics, metabolomics) of different diseases such as cancer, diabetes and infectious diseases using statistical machine learning
  • Bioinformatics and computational biology approaches
  • Biostatics and statistics study designs

Previous Experience

Dr. Halima Bensmail is Associate Professor at HBKU’s College of Public Health, a Senior Scientist of Biostatistics/Statistics and Computational Biology at the Qatar Computing Research Institute (QCRI), and founder of the Computational Biology group (CS&E) at QCRI. Dr. Bensmail's work focuses on developing new machine learning algorithms for solving large-scale and high-dimensional problems for achieving significant biomedical discoveries. Dr. Bensmail joined QCRI in 2011 while serving as an Associate Professor at the University of Virginia (EVMS) and an Adjunct Faculty member at Oak Ridge National Laboratory, USA. Before 2011, She held positions as Research Scientist at the Fred Hutchinson Cancer Research Center (FHCRC), USA and at the University of Leiden, The Netherlands; and as a Postdoctoral Researcher at the University of Washington, Statistics Department in Seattle, USA and as an Assistant and Associate Professor at the University of Tennessee in Knoxville, USA. Dr. Bensmail completed her PhD at the University Pierre et Marie-Curie (ParisVI). She serves as a consultant or advisory member for a number of key computational biology and biomedical engineering projects and grants agencies such as Qatar National Research Fund, Qatar Statistics Authority, American National Institute of Health (NIH), National Science Foundation (NSF) and Department of Energy (DOE). She has published numerous peer-reviewed manuscripts (+80) and has won multiple awards.

Professional Experience

  • University of Virginia Medical School, Biostatistics and Bioinformatics, Associate Professor, 2006
  • University of Tennessee, Statistics, Operations and management Sciences Department, Associate Professor, 2005
  • Oak Ridge National Laboratory, Adjunct faculty member, 2003
  • University of Tennessee, Statistics, Operations and management Sciences Department, Assistant Professor, 2000-2004
  • Data Theory Center, University of Social and Behavioral Sciences, Leiden, Netherlands, Scientist, 1997-2000
  • Fred Hutchinson Cancer Research Center Seattle, USA, Post-doc, 1996 -1997
  • University of Washington, Statistics Department, Seattle, USA, Research Associate, 1995-1996

Professional Associations and Awards

  • Qatar Annual Research Forum Award for best research subject in computing, Doha 2011.
  • Nominated and finalist for best researcher and teaching junior faculty member, Knoxville, 2005.
  • Best junior researcher award by IFCS (International Federation for Classification society), Rome, 1997.


  • PhD: Mathematics and Statistics, Paris 6 and INRIA (Paris - Rocquencourt), 1995.
  • MS: Mathematical Modeling, Paris 7, Paris, France, 1991.
  • BS: Mathematics, University of Sciences, Rabat, 1989.

Selected Research

  • Jing-Yang and Bensmail, H.  2013:  Cross-Domain Sparse Coding.  CIKM 2013.
  • Jing-Yang and Bensmail, H. 2012: Selecting and Weighting Visual Words Jointly for Bag-of-Features based Tissue Classification. BMC Bioinformatics.
  • Liu, Z and Bensmail, H. 2012: Phenotype Prediction and Feature Detection with Linear Programming and Metagenomics Count data. Plos One.
  • Liu, Z and Bensmail, H. 2012: Efficient Feature Selection and Multiclass Classification with Integrated Instance and Model based Learning.Journal of Evolutionary Biology.
  • Bensmail, H., Anjum, S., Bouhali, O. and Elanbari, M. 2012: RAFNI: Robust Analysis of Functional NeuroImages with nonnormal-stable error, in LNCS: Lecture Notes in computer science, Vol. 7663, subseries: Theoretical computer Science and General Issues.
  • Kwon, Y, Bozdogan, H. and Bensmail, H. 2009: Performance of Model Selection Criteria in Bayesian Threshold VAR (TVAR) Models. Econometric Reviews, Vol. 28 (1-3), pp. 83-101.
  • Bensmail H, Golek J, Moody MM, Semmes JO, Haoudi A. 2005: Bayesian Fast-Fourier Transform Based Clustering Method for Proteomics Data. Bioinformatics, 21(10), pp. 2210-24.
  • Bensmail, H. Celeux, G. Raftery, A., Robert, C. 1997. Inference in Model-Based Cluster Analysis. Journal of Computing and Statistics, 1, N10, pp.1-10.
  • Bensmail, H. & Celeux, G. 1996. Regularized Discriminant Analysis. Journal of the American Statistical Association (JASA), Vol. 91, No 436, pp. 1743—1748

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