Apply Online (June 08 - July 12,2020)


Click here for details

GIK Undergraduate Admissions,Fall Semester 2020. Click here for details
GIK Institute's measures against Coronavirus. Click here for details

FACULTY PROFILE

Engr. Rizwana Kalsoom

Research Associate
Email: rizwana.kalsoom@giki.edu.pk
Qualifications: MS Computer System Engineering
Research Interests: Machine Learning, Image Processing
Telephone: (Ext. 2307)

Education


  •  [2012-2013] MS in Computer System Engineering,  Ghulam Ishaq Khan Institute of Engineering Sciences and Technology, Topi
  •  [2007-2011] Bachelor of Science in Computer Engineering, University of Engineering & Technology, Taxila

Research Publications


  • Z. Halim, R. Kalsoom, S. Bashir, and G. Abbas, " Artificial intelligence techniques for driving safety and vehicle crash prediction," Artificial Intelligence Review, Vol. --, No. --, 201-. [ISSN: 0269-2821, Thomson Reuters JCR 2016, Impact factor 1.731, Springer]

 

  • Z.Halim, R. Kalsoom, and A. R. Baig, "Profiling drivers based on driver dependent vehicle driving features," Applied Intelligence, Vol. 44, No. 03, 2016, pp. 645-664. [ISSN: 0924-669X, Thomson Reuters JCR 2016, Impact factor 1.215, Springer]

 

  • R. Kalsoom, Z. Halim, "Clustering the Driving Features Based On Data Streams," 16th International Multi Topic Conference, INMIC13, Lahore, Pakistan, December 19-20, 2013.

 

Experience


  • Jan 2014 - Present:  Research Associate (Lecturer), GIK Institute, Pakistan.
    • Courses Taught:
      • Database management Systems
      • Signal and Systems
      • Computer Communications and Networking
      • Introduction to Programming
      • Intensive Programming
  • 2012 - 2013:  Graduate Assistantship at Ghulam Ishaq Khan Institute
    • Labs Instructed:
      • Introduction to Programming
      • Intensive Programming (Object Oriented Programming)

Honors and Memberships


  • Got GIK Institute Fully Funded Scholarship for MS in Computer System Engineering.
  • Registered Engineer with PEC (Registration No. COMP/8479).

MS Thesis


Early Warning System for Accident Prediction



Edit Profile