Nabil Belacel


Roles and responsibilities

Dr Belacel is a Senior Research Officer within Data Science for Complex Systems Team of Digital Technology Research Center, National Research Council of Canada. 

Current research and/or projects

Dr Belacel is conducting fundamental research on operation research and machine learning algorithms and their applications in decision support systems. 

Research and/or project statements

- Developing and applying preference modelling to decision support systems

-Developing and applying heuristics and metaheuristics for supervised and unsupervised learning methods

- Developing and applying graph theory algorithms


- PhD in operation research, Free University of Brussels, 1999

- Engineer in operation research, University of Science and Technology, Algiers, 1991 

Professional activities/interests

Adjunct professor, I have Supervising and co-supervising more than 10 graduate students

Succefully applied in several fundings as PI or co-applicant (NSERC, NBIF, AIF, Genome Canada)


EURO Working Group Multicriteria Decision Aiding


-Gold award of excellence from Canadian Information Productivity Awards in 2007 for the New strategy for gene expression-based biomarker discovery project.

- CATAAlliance Innovation and Leadership Award in the Public Sector Leadership in Advanced Technology category in 2009.


- Leading Scientific teams, November 20-22, 2006. Canada School of Public Service.

Inventions and patents

- US patent: US20070065856A1 Molecular method for diagnosis of prostate cancer (2007 )Inventors: N. Belacel, M. Cuperlovic-Culf, R. Ouellette

- US patent: US20110165582A1: Molecular method for diagnosis of colon cancer (2011) Inventors: N. Belacel, M. Cuperlovic-Culf, R. Ouellette

Key publications

Y. Djeddi, H. Ait Haddadene, N. Belacel (2019) An extension of adaptive multi-start tabu search for the maximum quasi-clique problem. Computers & Industrial Engineering 132 (2019): 280-292.

N. Belacel, M. Cuperlovic (2019) PROAFTN Classifier for Feature Selection with Application to Alzheimer Metabolomics Data Analysis, International Journal of Pattern Recognition and Artificial Intelligence.

F. Al-Obeidat, N. Belacel, B. Spencer (2019) Combining Machine Learning and Metaheuristics Algorithms for Classification Method PROAFTN. In book: Software Engineering Aspects of Continuous Development and New Paradigms of Software Production and Deployment, pp.53-79.

N. Belacel, G. Durand, S. Leger, B. Cajetan (2018) Scalable Collaborative Filtering Based on Splitting-Merging Clustering Algorithm, Agents and Artificial Intelligence, Lecture Notes in Computer Science book series (LNCS, volume 11352).

S. He, N. Belacel,  A Chan, H. Hamam, Y. Bouslimani  (2016) A Hybrid Artificial Fish Swarm Simulated Annealing Optimization Algorithm for Automatic Identification of Clusters, International Journal of Information Technology and Decision Making 15(05).

G. Durand, N. Belacel (2013) Graph theory based model for learning path recommendation, Information Science, 251:10-21.

N. Belacel, F. Al-Obeidat (2011) A Learning Method for Developing PROAFTN Classifiers and a Comparative Study with Decision Trees.Advances in Artificial Intelligence - 24th Canadian Conference on Artificial Intelligence, Canadian AI 2011.

F. Al Obeidat, N. Belacel et al. (2010) Differential Evolution for learning the classification method PROAFTN, Knowledge-Based Systems 23:418-426.

S. He, N. Belacel, H. Hamam, Y. Bouslimani (2009) Fuzzy clustering with improved artificial fish swarm algorithm. In 2009 International Joint Conference on Computational Sciences and Optimization (Vol. 2, pp. 317-321). IEEE.

N. Belacel, H.B. Raval, A.Punnen (2007). Learning multicriteria fuzzy classification method PROAFTN from data. Computers & Operations Research, 34(7), 1885-1898.

N. Belacel, Q. Wang, R. Richard (2006) Web-Integration PROAFTN Methodology for Acute Leukemia Diagnosis, Telemedicine and e-HealthVol. 11, No. 6:652-659.

N. Belacel, Q. Wang, M. Cuperlovic-Culf (2006) Clustering methods for microarray gene expression data. Omics: a journal of integrative biology, 10(4), 507-531.

N. Belacel, M. Čuperlović-Culf, M. Laflamme, R. Ouellette (2004). Fuzzy J-Means and VNS methods for clustering genes from microarray data. Bioinformatics, 20(11), 1690-1701.

N. Belacel, M.R. Boulassel (2004). Multicriteria fuzzy classification procedure PROCFTN: methodology and medical application. Fuzzy Sets and Systems, 141(2), 203-217.

N. Belacel, P. Hansen, N. Mladenovic (2002) Fuzzy J-means: a new heuristic for fuzzy clustering." Pattern Recognition 35/10, 2193-2200.

N. Belacel, M.R Boulassel (2001). Multicriteria fuzzy assignment method: a useful tool to assist medical diagnosis. Artificial intelligence in medicine, 21(1-3), 201-207.

Y. Guan, A. A. Ghorbani, N. Belacel (2003). Y-means: A clustering method for intrusion detection. In CCECE 2003-Canadian Conference on Electrical and Computer Engineering. Toward a Caring and Humane Technology (Cat. No. 03CH37436) (Vol. 2, pp. 1083-1086). IEEE.

Nabil Belacel (2000) Multicriteria assignment method PROAFTN: Methodology and medical application. European Journal of Operational Research 125/1:175-183.

Previous work experience

- May 2000-December 2001: Universite de Montreal, research associate

-Jan 2001-January 2002: Visual Decision Inc.  and DND: Quebec. Scientist Consultant

- October 1999-May 2000: Mathematics department and Saint Luc Hospital: Belgium,  Research Assistant

- September 1993-December 1994: Algerian Government, Computer Enginneer

- September 1991- June 1993: Algiers university, Teacher assistant

International experience and/or work

- 1995-2000: Research scientist and PhD student Free university of Brussels, Belgium

- 1999-2000- Research associate: Saint Luc Hospital Brussels, Belgium

Nabil Belacel

Nabil Belacel

Senior Research Officer
Digital Technologies
1200 Montreal Road
Ottawa, Ontario K1A 0R6
Preferred language: English
Other(s): Arabic, English, French
Telephone: 613-993-0182

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Information Technology, Artificial Intelligence, Clinical decision support systems , Machine Learning, Classification, Clustering, Optimization