Ms. Faria Nazir (PhD Scholar UET, Taxila)


Ms. Faria received her BS and MS degree in Software Engineering from University of Engineering and Technology (UET) Taxila. During MS, she started teaching at UET Taxila. After that she joined University of Lahore (UOL), Lahore campus and have been in academia since 2015. Currently, she is PhD Scholar at Software Engineering department, UET Taxila and working as Lecturer in Capital University of Science and Technology, Islamabad.

PhD Scholar Software Engineering University of Engineering & Technology, Taxila 2018
MS Software Engineering University of Engineering & Technology, Taxila 2015
BS Software Engineering University of Engineering & Technology, Taxila 2013
Lecturer Capital University of Science and Technology (CUST), Islamabad Since – 2019
Lecturer The University of Lahore, Lahore, Pakistan Since – 2018
Lecturer Barani Institute of Management Sciences, Rawalpindi Pakistan 2015 – 2015
Assistant Tutor/ Assistant Examiner University of Engineering & Technology, Taxila, Pakistan 2013 – 2015
Internship ID Technologies, Islamabad, Pakistan 2011 – 2011
1. Achieved Scholarship on getting top position in Software Engineering (5th, 6th and 7th Semester).
2. Award of Honor for securing CGPA more than 3.7 in BSc and MS Software Engineering.
3. Scholarship for MS – 15000 Rupees/month from UET Taxila
4. Participation certificate in UET Taxila projects exhibition “DJACE” (Development in Java Creativity Exhibition).
5. Certificate for attending workshop of Android.
1. “Social media signal detection using Tweets Volume, Hashtag, and Sentiment Analysis” published in Journal of multimedia tools and application, Springer.
2. “Security Management in Cloud Computing to Secure Cloud from Data Loss” published in International Journal of Knowledge, Innovation and Entrepreneurship.
3. “An Arabic mispronunciation detection system based on frequency of mistakes for Asian speakers” submitted in Journal of Artificial Intelligence Review.
4. “Mispronunciation Detection using Deep Convolutional Neural Network Features based Model for Arabic Phonemes” submitted in IEEE Access.

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