Assistant professor IT department NUML MULTAN.

Research Collaborator, Beijing University of Technology Dates of Engagement: 

Journal articles / reviews 1. Ali, Saqib, Sakhawat Ali, Syed Fakhar Bilal, Khalil ur Rehman, Zeeshan Shaukat, Ahmed Khan, and Rooha Khurram. "A robust U-net-based cascaded model for brain tumor substructures segmentation using magnetic resonance imaging." Cluster Computing 28, no. 7 (2025): 427. IF 4.1 2. Ali, Saqib, Rooha Khurram, Khalil ur Rehman, Anaa Yasin, Zeeshan Shaukat, Zareen Sakhawat, and Ghulam Mujtaba. "An improved 3D U-Net-based deep learning system for brain tumor segmentation using multi-modal MRI." Multimedia Tools and Applications 83, no. 37 (2024): 85027-85046. IF 2.685 3. Mahmood, Tariq, Jianqiang Li, Tanzila Saba, Amjad Rehman, and Saqib Ali. "Energy optimized data fusion approach for scalable wireless sensor network using deep learning-based scheme." Journal of Network and Computer Applications 224 (2024): 103841. IF 8.0 4. Shaukat, Zeeshan, Qurratul Ain Farooq, Chuangbai Xiao, Saqib Ali, Faheem Akhtar, Muhammad Azeem, and Abdul Ahad Zulfiqar. "Efficient scheme to perform semantic segmentation on 3-D brain tumor using 3-D u-net architecture." Multimedia Tools and Applications 83, no. 9 (2024): 25121-25134. IF 2.685 5. Ali, Saqib, Sana Sahiba, Muhammad Azeem, Zeeshan Shaukat, Tariq Mahmood, Zareen Sakhawat, and Muhammad Saqlain Aslam. "A recognition model for handwritten Persian/Arabic numbers based on optimized deep convolutional neural network." Multimedia tools and applications 82, no. 10 (2023): 14557-14580. IF 2.685 6. Liu, Rencheng, Saqib Ali, Syed Fakhar Bilal, Zareen Sakhawat, Azhar Imran, Abdullah Almuhaimeed, Abdulkareem Alzahrani, and Guangmin Sun. "An intelligent hybrid scheme for customer churn prediction integrating clustering and classification algorithms." Applied Sciences 12, no. 18 (2022): 9355. IF 2.5 7. Shaukat, Zeeshan, Qurat ul Ain Farooq, Shanshan Tu, Chuangbai Xiao, and Saqib Ali. "A state of-the-art technique to perform cloud-based semantic segmentation using deep learning 3D U-Net architecture." BMC bioinformatics 23, no. 1 (2022): 251. IF 3.3 8. Ali, Saqib, Jianqiang Li, Yan Pei, Rooha Khurram, Khalil Ur Rehman, and Tariq Mahmood. "A comprehensive survey on brain tumor diagnosis using deep learning and emerging hybrid techniques with multi-modal MR image." Archives of computational methods in engineering 29, no. 7 (2022): 4871-4896. IF 12.1 9. Rehman, Khalil ur, Jianqiang Li, Yan Pei, Anaa Yasin, Saqib Ali, and Yousaf Saeed. "Architectural distortion-based digital mammograms classification using depth wise convolutional neural network." Biology 11, no. 1 (2021): 15. IF 3.5 10. Ali, Saqib, Jianqiang Li, Yan Pei, Rooha Khurram, Khalil ur Rehman, and Abdul Basit Rasool. "State-of-the-art challenges and perspectives in multi-organ cancer diagnosis via deep learning based methods." Cancers 13, no. 21 (2021): 5546. IF 4.4 11. Rehman, Khalil Ur, Jianqiang Li, Yan Pei, Anaa Yasin, Saqib Ali, and Tariq Mahmood. "Computer vision-based microcalcification detection in digital mammograms using fully connected depthwise separable convolutional neural network." Sensors 21, no. 14 (2021): 4854. IF 3.5 12. Ali, Saqib, Jianqiang Li, Yan Pei, Muhammad Saqlain Aslam, Zeeshan Shaukat, and Muhammad Azeem. "An effective and improved CNN-ELM classifier for handwritten digits recognition and classification." Symmetry 12, no. 10 (2020): 1742. IF 2.2 13. Shaukat, Zeeshan, Saqib Ali, Qurat ul Ain Farooq, Chuangbai Xiao, Sana Sahiba, and Allah Ditta. "Cloud-based efficient scheme for handwritten digit recognition." Multimedia Tools and Applications 79, no. 39 (2020): 29537-29549. IF 2.685 14. Ali, Saqib, Zeeshan Shaukat, Muhammad Azeem, Zareen Sakhawat, Tariq Mahmood, and Khalil ur Rehman. "An efficient and improved scheme for handwritten digit recognition based on convolutional neural network." SN Applied Sciences 1, no. 9 (2019): 1125. IF 2.4 15. Mahmood, Tariq, Faheem Akhtar, Sher Daudpota, Khalil ur Rehman, Saqib Ali, and Fawaz Mahiuob Mokbal. "A comprehensive survey on the performance analysis of underwater wireless sensor networks (UWSN) routing protocols." International Journal of Advanced Computer Science and Applications 10, no. 5 (2019). IF 0.9

E.4. Articles Under review 1. 2. Muhammad Arif, Jianqiang Li, Jun Qian, Saqib Ali, and Syed Fakhar Bilal “Predictive Antenatal Models: A Systematic Review of Advanced Approaches for Forecasting Fetal Weight, Delivery Mode, and Fetal Gender.” Neurocomputing. (Major revision submitted) IF 6.5 Syed Fakhar Bilal, Jianqiang Li, Jun Qian, Saqib Ali, Rooha Khurram, and Muhammad Arif “Evolution of Brain Tumor Segmentation: A Multimodal Imaging Analysis from Machine Learning to Emerging Trends (2014-2025).” Neurocomputing. (Major revision submitted) IF 6.5 E.5. Scientific meetings/ conferences and book chapters 1. Ali, Saqib, Jianqiang Li, Yan Pei, and Khalil Ur Rehman. "A multi-module 3d u-net learning architecture for brain tumor segmentation." In International Conference on Data Mining and Big Data, pp. 57-69. Singapore: Springer Nature Singapore, 2022. Oral Presentation 2. ur Rehman, Khalil, Jianqiang Li, Yan Pei, Anaa Yasin, and Saqib Ali. "A Deep Learning-Based Approach for Mammographic Architectural Distortion Classification." In International Conference on Innovative Computing, pp. 3-14. Singapore: Springer Nature Singapore, 2022. 3. ur Rehman, Khalil, Jianqiang Li, Yan Pei, Anaa Yasin, Saqib Ali, and Yousaf Saeed. "A feature fusion-based approach for mammographic mass classification using deep learning." In International Conference on Innovative Computing, pp. 62-73. Singapore: Springer Nature Singapore, 2022. 4. Ali, Saqib, Zareen Sakhawat, Tariq Mahmood, Muhammad Saqlain Aslam, Zeeshan Shaukat, and Sana Sahiba. "A robust CNN model for handwritten digits recognition and classification." In 2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA), pp. 261-265. IEEE, 2020. 5. Sakhawat, Zareen, Saqib Ali, and Liu Hongzhi. "Handwritten digits recognition based on deep learning4J." In Proceedings of the 2018 International Conference on Artificial Intelligence and Pattern Recognition, pp. 21-25. 2018. 6. Shaukat, Zeeshan, Juan Fang, Muhammad Azeem, Faheem Akhtar, and Saqib Ali. "Cloud based face recognition for google glass." In Proceedings of the 2018 International conference on computing and artificial intelligence, pp. 104-111. 2018. 7. Fang, Juan, Zeeshan Shaukat, Saqib Ali, and Abdul Ahad Zulfiqar. "Cloud computing: virtual web hosting on infrastructure as a service (IAAS)." In International Conference on Mobile Ad Hoc and Sensor Networks, pp. 450-460. Singapore: Springer Singapore, 2017.

• Artificial Intelligence,
• Machine Learning, 
• Medical Image Analysis

Education

• PhD - Software Eng. (2018 - 2023) College of Software Engineering, Beijing University of Technology (BJUT), Beijing China (CN)
• Master - Software Eng. (2016 - 2018) College of Software Engineering, Beijing University of Technology (BJUT), Beijing China (CN)
• Bachelor - Business (2009 - 2012) University of the Punjab/ PK

Experience

Assistant professor IT department NUML MULTAN.

Research Collaborator, Beijing University of Technology Dates of Engagement: 

Publications

Journal articles / reviews 1. Ali, Saqib, Sakhawat Ali, Syed Fakhar Bilal, Khalil ur Rehman, Zeeshan Shaukat, Ahmed Khan, and Rooha Khurram. "A robust U-net-based cascaded model for brain tumor substructures segmentation using magnetic resonance imaging." Cluster Computing 28, no. 7 (2025): 427. IF 4.1 2. Ali, Saqib, Rooha Khurram, Khalil ur Rehman, Anaa Yasin, Zeeshan Shaukat, Zareen Sakhawat, and Ghulam Mujtaba. "An improved 3D U-Net-based deep learning system for brain tumor segmentation using multi-modal MRI." Multimedia Tools and Applications 83, no. 37 (2024): 85027-85046. IF 2.685 3. Mahmood, Tariq, Jianqiang Li, Tanzila Saba, Amjad Rehman, and Saqib Ali. "Energy optimized data fusion approach for scalable wireless sensor network using deep learning-based scheme." Journal of Network and Computer Applications 224 (2024): 103841. IF 8.0 4. Shaukat, Zeeshan, Qurratul Ain Farooq, Chuangbai Xiao, Saqib Ali, Faheem Akhtar, Muhammad Azeem, and Abdul Ahad Zulfiqar. "Efficient scheme to perform semantic segmentation on 3-D brain tumor using 3-D u-net architecture." Multimedia Tools and Applications 83, no. 9 (2024): 25121-25134. IF 2.685 5. Ali, Saqib, Sana Sahiba, Muhammad Azeem, Zeeshan Shaukat, Tariq Mahmood, Zareen Sakhawat, and Muhammad Saqlain Aslam. "A recognition model for handwritten Persian/Arabic numbers based on optimized deep convolutional neural network." Multimedia tools and applications 82, no. 10 (2023): 14557-14580. IF 2.685 6. Liu, Rencheng, Saqib Ali, Syed Fakhar Bilal, Zareen Sakhawat, Azhar Imran, Abdullah Almuhaimeed, Abdulkareem Alzahrani, and Guangmin Sun. "An intelligent hybrid scheme for customer churn prediction integrating clustering and classification algorithms." Applied Sciences 12, no. 18 (2022): 9355. IF 2.5 7. Shaukat, Zeeshan, Qurat ul Ain Farooq, Shanshan Tu, Chuangbai Xiao, and Saqib Ali. "A state of-the-art technique to perform cloud-based semantic segmentation using deep learning 3D U-Net architecture." BMC bioinformatics 23, no. 1 (2022): 251. IF 3.3 8. Ali, Saqib, Jianqiang Li, Yan Pei, Rooha Khurram, Khalil Ur Rehman, and Tariq Mahmood. "A comprehensive survey on brain tumor diagnosis using deep learning and emerging hybrid techniques with multi-modal MR image." Archives of computational methods in engineering 29, no. 7 (2022): 4871-4896. IF 12.1 9. Rehman, Khalil ur, Jianqiang Li, Yan Pei, Anaa Yasin, Saqib Ali, and Yousaf Saeed. "Architectural distortion-based digital mammograms classification using depth wise convolutional neural network." Biology 11, no. 1 (2021): 15. IF 3.5 10. Ali, Saqib, Jianqiang Li, Yan Pei, Rooha Khurram, Khalil ur Rehman, and Abdul Basit Rasool. "State-of-the-art challenges and perspectives in multi-organ cancer diagnosis via deep learning based methods." Cancers 13, no. 21 (2021): 5546. IF 4.4 11. Rehman, Khalil Ur, Jianqiang Li, Yan Pei, Anaa Yasin, Saqib Ali, and Tariq Mahmood. "Computer vision-based microcalcification detection in digital mammograms using fully connected depthwise separable convolutional neural network." Sensors 21, no. 14 (2021): 4854. IF 3.5 12. Ali, Saqib, Jianqiang Li, Yan Pei, Muhammad Saqlain Aslam, Zeeshan Shaukat, and Muhammad Azeem. "An effective and improved CNN-ELM classifier for handwritten digits recognition and classification." Symmetry 12, no. 10 (2020): 1742. IF 2.2 13. Shaukat, Zeeshan, Saqib Ali, Qurat ul Ain Farooq, Chuangbai Xiao, Sana Sahiba, and Allah Ditta. "Cloud-based efficient scheme for handwritten digit recognition." Multimedia Tools and Applications 79, no. 39 (2020): 29537-29549. IF 2.685 14. Ali, Saqib, Zeeshan Shaukat, Muhammad Azeem, Zareen Sakhawat, Tariq Mahmood, and Khalil ur Rehman. "An efficient and improved scheme for handwritten digit recognition based on convolutional neural network." SN Applied Sciences 1, no. 9 (2019): 1125. IF 2.4 15. Mahmood, Tariq, Faheem Akhtar, Sher Daudpota, Khalil ur Rehman, Saqib Ali, and Fawaz Mahiuob Mokbal. "A comprehensive survey on the performance analysis of underwater wireless sensor networks (UWSN) routing protocols." International Journal of Advanced Computer Science and Applications 10, no. 5 (2019). IF 0.9

E.4. Articles Under review 1. 2. Muhammad Arif, Jianqiang Li, Jun Qian, Saqib Ali, and Syed Fakhar Bilal “Predictive Antenatal Models: A Systematic Review of Advanced Approaches for Forecasting Fetal Weight, Delivery Mode, and Fetal Gender.” Neurocomputing. (Major revision submitted) IF 6.5 Syed Fakhar Bilal, Jianqiang Li, Jun Qian, Saqib Ali, Rooha Khurram, and Muhammad Arif “Evolution of Brain Tumor Segmentation: A Multimodal Imaging Analysis from Machine Learning to Emerging Trends (2014-2025).” Neurocomputing. (Major revision submitted) IF 6.5 E.5. Scientific meetings/ conferences and book chapters 1. Ali, Saqib, Jianqiang Li, Yan Pei, and Khalil Ur Rehman. "A multi-module 3d u-net learning architecture for brain tumor segmentation." In International Conference on Data Mining and Big Data, pp. 57-69. Singapore: Springer Nature Singapore, 2022. Oral Presentation 2. ur Rehman, Khalil, Jianqiang Li, Yan Pei, Anaa Yasin, and Saqib Ali. "A Deep Learning-Based Approach for Mammographic Architectural Distortion Classification." In International Conference on Innovative Computing, pp. 3-14. Singapore: Springer Nature Singapore, 2022. 3. ur Rehman, Khalil, Jianqiang Li, Yan Pei, Anaa Yasin, Saqib Ali, and Yousaf Saeed. "A feature fusion-based approach for mammographic mass classification using deep learning." In International Conference on Innovative Computing, pp. 62-73. Singapore: Springer Nature Singapore, 2022. 4. Ali, Saqib, Zareen Sakhawat, Tariq Mahmood, Muhammad Saqlain Aslam, Zeeshan Shaukat, and Sana Sahiba. "A robust CNN model for handwritten digits recognition and classification." In 2020 IEEE International Conference on Advances in Electrical Engineering and Computer Applications (AEECA), pp. 261-265. IEEE, 2020. 5. Sakhawat, Zareen, Saqib Ali, and Liu Hongzhi. "Handwritten digits recognition based on deep learning4J." In Proceedings of the 2018 International Conference on Artificial Intelligence and Pattern Recognition, pp. 21-25. 2018. 6. Shaukat, Zeeshan, Juan Fang, Muhammad Azeem, Faheem Akhtar, and Saqib Ali. "Cloud based face recognition for google glass." In Proceedings of the 2018 International conference on computing and artificial intelligence, pp. 104-111. 2018. 7. Fang, Juan, Zeeshan Shaukat, Saqib Ali, and Abdul Ahad Zulfiqar. "Cloud computing: virtual web hosting on infrastructure as a service (IAAS)." In International Conference on Mobile Ad Hoc and Sensor Networks, pp. 450-460. Singapore: Springer Singapore, 2017.

Interests

• Artificial Intelligence,
• Machine Learning, 
• Medical Image Analysis