Research Interests

  • Study of greedy and dynamic programming algorithms for construction of exact and approximate decision trees, rules and reducts for decision tables with many-valued decisions
  • Analysis and design of classifiers based on decision trees, reducts, and decision rule systems
  • Data mining, Machine Learning

Selected Publications

  • Mohammad Azad, Igor Chikalov, Shahid Hussain and Mikhail Moshkov. “Restricted multi-pruning of decision trees”. MLDAS (Machine Learning and Data Analytics Symposium) 2016 organized by QCRI (Qatar Computing Research Institute) and Boeing International, Doha, Qatar (best contributed paper).
  • Mohammad Azad, Igor Chikalov, Shahid Hussain, and Mikhail Moshkov. Multi-pruning of decision trees for knowledge representation and classification. The 3rd IAPR Asian Conference on Pattern Recognition (ACPR), IEEE, pages 604 - 608, 2015.
  • Mohammad Azad and Mikhail Moshkov. Minimization of decision tree average depth for decision tables with many-valued decisions. Procedia Computer Science, 35:368 - 377, 2014.
  • Mohammad Azad, Igor Chikalov, and Mikhail Moshkov. Three approaches to deal with inconsistent decision tables -- comparison of decision tree complexity. In 14th International Conference on Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing (RSFDGrC 2013), pages 46 - 54, Springer, 2013.
  • Mohammad Azad, Igor Chikalov, Mikhail Moshkov, Beata Zielosko. Greedy algorithm for construction of decision trees for tables with many-valued decisions. In Louchka Popova-Zeugmann, editor, Proceedings of the 21th International Workshop on Concurrency, Specification and Programming, Berlin, Germany, September 26-28, 2012.

Education

  • M.S., King Abdullah University of Science and Technology, 2011
  • B.S., Bangladesh University of Engineering and Technology, 2007