Majid Khawar

Brief Bio

Majid Khawar is a Lecturer in the Faculty of Computer Science & Information Technology at the University of Southern Punjab, Multan, with extensive academic and industry experience in computer science education and software development. His expertise spans Artificial Intelligence, Machine Learning, Data Science, and Software Engineering.

He has actively contributed to Outcome-Based Education (OBE), Quality Enhancement Cell (QEC) processes, and curriculum development. His research focuses on AI applications in healthcare, predictive analytics, and emerging computing technologies. He is also engaged in teaching, mentoring, and academic development activities to enhance student learning outcomes.

Education
MS Computer Science
NFC Institute of Engineering & Technology, Multan
2020
BS Software Engineering
Riphah International University, Islamabad
2017
Professional Experience
Lecturer
University of Southern Punjab, Multan
2023 – Till now
Visiting Instructor
Pakistan National Youth (PNY), Multan
2023 – Till now
Visiting Lecturer
Multan Institute of Technology
2024 – Till now
Lecturer
Ideal Degree College, Muzaffargarh
2023
Lecturer
City College of Science & Commerce (University Campus), Multan
2021 – 2023
Lecturer
University College of Management & Sciences, Khanewal
2019 – 2021
Software Engineer
System Teknologies International (STI), Islamabad
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Professional associations

  • Member, Academic & Curriculum Development Committees (USP) 
  • Contributor to OBE and QEC Academic Quality Processes

Research Interests

  • Artificial Intelligence & Machine Learning
  • Data Science & Predictive Analytics
  • Deep Learning & Computer Vision
  • Healthcare Informatics
  • Big Data Technologies

Current Projects

  • AI-based disease prediction models 
  • Generative AI applications in education and healthcare

Research Impact:

  • Publications: 7+ 
  • Active Research Collaborations: National
Title Year Published Link
Generative AI–Based Multilingual Multimodal Framework for Depression Detection
2026
Click to view
Generative Artificial Intelligence and Personalized Learning
2025
Click to view
Climate Change Forecasting Using Time Series Techniques
2025
Click to view
Agile Ontology Development Framework
2024
Click to view
Security Issues of IoT in Healthcare Sector
2022
Click to view
Big Data in Healthcare: Systematic Review
2021
Click to view
Machine Learning in Breast Cancer Prediction
2020
Click to view

Khawar, M., Ashraf, U., Ghous, H., & Malik, M. H. (2026). Generative AI–based multilingual multimodal framework for depression detection. Southern Journal of Computer Science, 2(1), 43–65.

Khawar, M., Mohamed, F. N., Azhar, J., Yasmeen, S., & Hussain, I. (2025). Generative artificial intelligence and personalized learning. Southern Journal of Computer Science, 1–36.

Khawar, M., Ghous, H., Malik, A., Ahmad, Z., & Jabeen, U. (2025). Climate change forecasting using time series techniques. Southern Journal of Computer Science, 1(1), 37–61.

Khawar, M., Raza, A., Ali, M. I., Niaz, Q., & Asif, M. (2024). Agile ontology development: A comprehensive framework from preliminary investigations to evaluation. Journal of Computers and Intelligent Systems, 2, 33–51.

Khawar, M., Ahmed, M. M., Mahboob, R. M. M., Jahangir, H., & Imam, M. (2022). Security issues of IoT in healthcare sector: A systematic review. In Soft Computing for Security Applications (Vol. 1397). Springer, Singapore.

Khawar, M., Mahboob, R. M. M., Ahmed, M. M., & Imam, M. (2021). Benefits and challenges of big data in healthcare: A systematic review of Pakistan initiatives. International Journal of Current Research, 8(5), 1173.

Khawar, M., Aslam, N., Mahboob, R. M. M., Ahmed, M. M., Jahangir, H., & Mughal, A. (2020). Comparative study of machine learning algorithms in breast cancer prognosis and prediction. International Journal of Computer Science and Network Security, 20(8), 125.

Teaching & Supervision

Courses:

  • Programming Fundamentals 
  • Object-Oriented Programming 
  • Database Systems 
  • Software Engineering 
  • Artificial Intelligence 
  • Python Programming 
  • Software Project Management 
  • Computer Organization & Assembly Language

Supervision:

  • More than 20 Student Supervise in BSCS Program

Teaching Philosophy

To integrate theoretical knowledge with practical applications, enabling students to solve real-world problems using modern computing technologies.

Projects & Thesis

MS Thesis:
Comparative Study of Machine Learning Applications in Cancer Prediction

Key Projects:

  • Disease Prediction System (ML) 
  • Facial Recognition using CNN & MTCNN 
  • Distributed Memory Schema (.NET WCF) 
  • Library Management System (ASP.NET + SQL) 
  • Online Shopping System with Payment Integration

Technical Skills

AI & Data Science:
Machine Learning, Deep Learning, Computer Vision, NLP

Programming Languages:
Python, R, C, C++, C#, SQL, PHP

Web Technologies:
HTML, CSS, JavaScript, ASP.NET

Databases:
SQL Server, MySQL, Oracle, MongoDB

Tools:
Anaconda, Jupyter, Google Colab, Hadoop, Spark, Tableau

Certifications & Workshops

  • Best Instructor Award (AI & ML) – PNY (2025) 
  • Huawei Certified Instructor 
  • Routing & Switching Certification 
  • Faculty Development Workshops (Teaching & Learning) 
  • English Language Certification (IIUI)

Awards & Recognition

  • Best Instructor Award – AI & Machine Learning (PNY, 2025)

Collaboration

Open to research collaborations in Artificial Intelligence, Data Science, and interdisciplinary computing applications.

Contact