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

Most importantly, Halima is focusing on:

• Use of machine learning for genetic mapping,
• Bayesian approach to Quantification of metabolites related to diseases such as diabetes.
• Covariance matrix robustness in graphical models and networks
• Topology of causal network.
• Nonlinear statistical analysis in NeuroImages.

Halima Bensmail is an Associate Professor of Mathematics at the University of Tennessee and an adjunct faculty member at ORNL. She received her PhD in Mathematics and statistics from the University of Jussieu and INRIA in December 1995. She holds a BS degree in Mathematics from University of Science, Rabat and a MS degree of Mathematics and statistics from the University of Jussieu, Paris, France. She spent one year at the University of Washington, one year at the Fred Hutchinson cancer research center and two years at the Data Theory center, at the University of Leiden, the Netherlands. She advised five PhD students and over 20 Master students in different field of mathematical and computational sciences.

• 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

• 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.

• International Federation for Classification Society (IFCS) (http://www.classification-society.org/ifcs/)
• International Society for Bayesian Analysis (ISBA) http://bayesian.org/
• TTI/VANGUARD (www.ttivanguard.com).

• 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.

• 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