Mr. Muhammad Abdullah Ilyas

Lecturer (CS)

Muhammad Abdullah Ilyas is a highly accomplished academic and professional in the field of Computer Science, currently serving as a lecturer at Qarshi University in Lahore. He is a Ph.D. scholar and holds a degree in M.Phil. in Computer Science from Punjab University College of Information Technology (PUCIT), and a B.Sc. in Computer Science from the University of Engineering and Technology (UET), Lahore. With a robust background in software development, he has extensive experience working with technologies such as PHP, JavaScript, MySQL, and various CRM systems including SugarCRM, SuiteCRM, and X2CRM. During his tenure at RolusTech and Velorium, he developed expertise in integrating complex systems and automating business processes. His notable projects include the development of automation solutions for Pharox Laboratory and US-Pharmacy, among others. Mr. Ilyas has also contributed to academia as an adjunct faculty member at PUCIT and has published research on emotion detection in multilingual text. His diverse skill set encompasses programming, database management, and web engineering, alongside strong communication and adaptability skills, making him a valuable asset in both academic and professional settings.


  • Phil (CS), PUCIT, PU, Lahore, 2015
  • BSCS, UET, Lahore, 2013


  1. Lecturer, Qarshi University                                                                      (Jan 2020 to present)

Courses: Web Engineering, OOP, PFA, Algorihms

  1. Adjunct faculty member at PUCIT (Contract)                                       (2014 to 2016)

Courses: Database Theory + lab, Introduction to Computing

  1. Software Developer, RolusTech(pvt.) Ltd.                                       (June 2016 to Dec 2019)
  • Worked on PHP, CSS, Java Script, MYSQL database, SEO (Search Engine Optimization), HTML, JQUERY,SugarCRM,SuiteCRM,X2CRM, Mailchimp, Stripe,Altova Softwares.



  • Ilyas, A., Shahzad, K., & Kamran Malik, M. (2023). Emotion detection in code-mixed roman urdu-english text. ACM Transactions on Asian and Low-Resource Language Information Processing22(2), 1-28.
  • Ilyas, M. A., & Shahzad, K. (2021). Urdu Fake News Detection using TF-IDF Features and Text CNN. In FIRE (Working Notes)(pp. 1135-1141).
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