Dr. Saif Ur Rehman
Assistant Professor

Ph.D, MS, MCS (Gold Medalist)
University Institute of Information Technology
Phone : 051-9292195  
Cell : 03435802355  
Fax :
Email : [email protected]
Address : University Institute of Information Technology, PMAS-Arid Agriculture University Rawalpindi
Work Experience : 14 Year(s)
Research Interest :
  • Graph Mining
  • Data Mining
  • Social Network Analysis
  • Databases
  • Programming Languages (C; C++; Java; Microsoft .Net Technologies; Oracle etc)
  • Total Publications : 20
    Publications (Latest Ten)
    1. S. Rehman, S. Asghar, (March, 2019): "A-RAFF: A Ranked Frequent FP-Growth Subgraph Pattern Discovery Approach," Accepted for Publication in Journal of Internet Technology, March 2019, Vol. 20, No. 2, ISSN= 1607-9264 (Thomson Reuters Master Journal List, Impact Factor: 1.301).

    2. A-RAFF: A Ranked Frequent FP-Growth Subgraph Pattern Discovery Approach, Published V (20), No. 1, PP. 257-267. Journal of Internet Technology, 2018, ISSN:1607-9264 (Thomson Reuters Master Journal List, IF = 1.301)

    3. An Efficient Ranking Scheme for Frequent Subgraphs, Published in ACM 10th ICMLC, PP. 257-262 , February 26-28, 2018, University of Macau, Taipa, Macau, SAR.

    4. S. Jameel and S. Rehman, (2018): "An optimal feature selection method using a modified wrapper based Ant Colony Optimization," Published Journal of the National Science Foundation, ISSN= 139-4588 , (Thomson Reuters Master Journal List, Impact Factor: 0.42), Vol. 46. No. 2, 2018.

    5. M. Iqbal, and S. Rehman, (June, 2018): "Association Rule Mining Using Computational Intelligence Technique," Published in International Journal of Computer Science and Information Security (IJCSIS), Vol. 14, No.12, pp. 416-424, ISSN: 1947-5500, (Thomson Reuters Master Journal List).

    6. M. Iqbal, S. Rehman, S. Gillani and S. Asghar, (January, 2015): An Empirical Evaluation of Feature Selection Methods. Improving Knowledge Discovery through the Integration of Data Mining Techniques. Book Chapter, Advances in Data Mining and Database Management (ADMDM) Book Series, IGI Global.

    7. Performance Evaluation of Frequent Subgraph Discovery Techniques, Publishedin Mathematical Problems in Engineering, Vol. 2014, Article ID 869198, 6 pages, 2014. doi:10.1155/2014/869198, Thomson Reuters Master Journal List, IF = 1.179.

    8. S. Rehman, S. Asghar, (2014): "Performance evaluation of frequent subgraph discovery techniques," Published In Mathematical Problems in Engineering, vol. 2014. ISSN=1024-123X. (Thomson Reuters Master Journal List, Impact Factor: 0.802).

    9. S. Rehman, A. Haider, T. Afzal, and K. Aziz, (2014). Measuring the Relevancy between Tags and Citation in Social Web. Research Journal of Applied Sciences, Engineering and Technology, 7(24), 5172-5178.

    10. A. Z. Khan, S. Rehman, H. Israr, & K. Aziz, (2014) "An Enhanced Multi Density based Clustering Technique using density level Partition (EDSCANDLP), Journal of Scientific Research, 120(2).