Maryem Ismail

Brief Bio

Maryem Ismail is a Lecturer in Computer Science at the University of Southern Punjab, Multan, with research expertise in computer vision, image processing, and machine learning. Her work primarily focuses on applying artificial intelligence techniques to biomedical imaging and public health challenges, particularly in disease detection and analysis using medical imaging data.

She has contributed to multiple peer-reviewed publications in the domains of machine learning, healthcare analytics, and image-based disease classification. Her research includes studies on COVID-19 detection using CT images, vaccine hesitancy analysis, and early breast cancer detection using machine learning models.

At the University of Southern Punjab, she is actively involved in teaching, research supervision, and departmental academic activities, contributing to the development of innovative and applied research solutions in computing.

Education
PhD (Computer Science)
University of Southern Punjab Multan
In Progress
Master of Science in Computer Science
National College of Business Administration & Economics (NCBA&E), Lahore
2024
Master of Science in Information Technology
University of Education, Lahore
2016
Professional Experience
Senior Lecturer
University of Southern Punjab, Multan
2022 – Till now
Lecturer
University of Southern Punjab, Multan
2017 – 2022
Lecturer
RISE Group of Colleges, Multan
2016 – 2017

Research Interests

  • Artificial Intelligence
  • Machine Learning
  • Deep Learning
  • Computer Vision
  • Image Processing

Current Projects

  • Lens Mart E-commerce store with virtual Try on
  • Retinal-Based Attendance System
  • AI -Based facial recognition system for secure access control
  • Emotion recognition from speech using machine learning
  • Rice classification using ML Methods
  • QR- Based Attendance system
  • OBE-based system for an educational institute

Research Impact:

  • Publications: 10+
  • h-index:
  • Funded Projects: None
Title Year Published Link
Textual Analysis of Vaccine Hesitancy Trends During the COVID-19 Pandemic
2025
Click to view
Market Basket Analysis for Next Basket Item Prediction Using Machine Learning
2024
Click to view
Machine Learning-Based Classification of Chest Diseases Using CT Images
2024
Click to view
Detection of Neuromuscular Disorders Using Electromyography
2023
Click to view
Thunderstorms Prediction Using Satellite Images
2023
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AI-Based Lane Detection Using Satellite Images
2021
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Review on DeepFake Video Detection Techniques
2023
Click to view
Early Detection of Breast Cancer Tumors Using LDA
2022
Click to view
Saraiki Language Hybrid Stemmer Using LSTM
2022
Click to view
  1. Maryem Ismail, Qasim Niaz, Imran Ali, Shakeeb Khan, Hina Mehboob (2025)Textual Analysis of Vaccine Hesitancy Trends During The COVID-19 Pandemic
  2. Malik, M. H., Ghous, H., Maryem Ismail, M., Jamshaid, S., & Altaf, J. (2024). Market Basket Analysis for Next Basket Item Prediction Using Data Mining and Machine Learning. Journal of Computing & Biomedical Informatics.
  3. Malik, M. H., Ghous, H., Maryem Ismail, M., Nawaz, S. A., & Ijaz, H. M. (2024). A Machine Learning-Based Classification of Chest Diseases Using Computed Tomography Images. Journal of Computing & Biomedical Informatics.
  4. Maryem Ismail, M., Batool, S., Khan, M. H., Ali, I., & Haider, Z. (2023). Review on the Detection of Multiple Neuromuscular Disorder Using Electromyography. Southern Journal of Engineering & Technology, 1(02), 46-68.
  5. Amjad, K., Malik, M., Ghous, H., Hussain, A., Maryem Ismail, (2023). Thunderstorms Prediction Using Satellite Images. International Journal of Information Systems and Computer Technologies,
  6. Rehman, I., Ghous, H., Malik, M,Maryem Ismail, M. (2023). Artificial Intelligence-based Lane Detection using Satellite Images. International Journal of Information Systems and Computer Technologies,
  7. Ghous, H., Malik, M., Maryem Ismail, M. (2023). Review on DeepFake Video Detection Techniques.
  8. Ghous, H., Malik, M., Abbas, Maryem Ismail, M. (2022). Early Detection of Breast Cancer Tumors Using Linear Discriminant Analysis Feature Selection with Different Classification Methods. International Journal of Information Systems and Computer Technologies,
  9. Malik, M. H., Ghous, H., Ahsan, Maryem Ismail, M. (2022). Saraiki Language Hybrid Stemmer Using Rule-Based and LSTM-Based Sequence-To-Sequence Model Approach. Innovative Computing Review.

Teaching & Supervision

Courses:

  • Image Processing
  • Computer Vision
  • Artificial Intelligence
  • Core Computer Science Courses

Supervision:

  • FYP Projects Bachelors: 12

Teaching Philosophy

Focused on integrating theoretical knowledge with practical applications, enabling students to solve real-world problems using modern computational techniques and research-driven learning.

Collaborations and Honors

  • Women Ambassador Award from University of Southern Punjab, Multan

Collaboration

Open to academic and research collaborations in artificial intelligence, machine learning, and medical image analysis.

Contact