HINDAWI Mohammed
Researcher-lecturer
Research interest
Data Mining, Big data, (Fuzzy, collaborative, on-line, incremental) Clustering, (Semi-supervised, Unsupervised, Supervised) Learning, Dimensionality Reduction (Feature Selection and Extraction), Ensemble Methods.
Educational activities
- Discipline : Computer Science (Embedded Systems, Object-Oriented Programming, Database Management Systems, AI, Advanced algorithms)
- Activities : educational tutoring engineering students, educational design
Background
PhD in Computer Science
National Institute of Applied Sciences (INSA), Lyon
« Feature Selection for Semi-Supervised Data Analysis in Decisional Information Systems »
Master of Research
National Institute of Applied Sciences (INSA), Lyon
Knowledge and Decision
Master of Science
University, Syria
Software Engineering and Information Systems Aleppo
Bachelor of Science
University, Syria
Computer science – Software Engineering and Information Systems Aleppo
Current Research Program
Dimensionality Reduction in semi-supervised learning
Scientific animation
- Advanced Automation: IA and Data science.
- Member of research group : frugal et embedded IA
Publications
- 3 papers in international journals
- 7 papers in international conferences
- 2 papers in national conferences
- 1 PhD thesis
- 1 Master thesis
Selected publications
- Khalid Benabdeslem, Haytham Elghazel, Mohammed Hindawi, ”Ensemble constrained Laplacian score for efficient and robust semi-supervised feature selection.,” Knowledge and Information Systems KAIS, 49(3) : 1161-1185 (2016)
- Khalid Benabdeslem, Mohammed Hindawi, Raywat Makkhongkaew, ”Weighting Based Approach for Semi-supervised Feature Selection.,” (ICONIP 2015) : 300-307
- Khalid Benabdeslem, Mohammed Hindawi, ”Efficient Semi-supervised Feature Selection: Constraint, Relevance and Redundancy,” IEEE Transactions on Knowledge and Data Engineering TKDE, 26(5): 1131-1143 (2014). IEEE computer Society Digital Library. IEEE Computer Society.
- Mohammed Hindawi, Khalid Benabdeslem, ”Local-to-Global Semi-Supervised Feature Selection”. Accepted by 22nd ACM International Conference on Information and Knowledge Management (CIKM 2013)
- M. Hindawi, K. Allab, K. Benabdeslem. Constraint selection based semi-supervised feature selection. In the proceeding of ICDM. IEEE International Conference on Data Mining, pp 1080-1085, 11-14 December 2011