Dr. Muhammad Shahid Iqbal ( Assistant Professor )

Department of Computer Science & Information Technology

Machine Learning, Deep Learning, Computational Pathology, Digital Pathology, Microscopy Image Analysis and Medical Imaging

Ph.D. (Computer Science)

Nawabi, Awais Khan, Sheng Jinfang, Rashid Abbasi, Muhammad Shahid Iqbal, Md Belal Bin Heyat, Faijan Akhtar, Kaishun Wu, and Baidenger Agyekum Twumasi."Segmentation of Drug-Treated Cell Image and Mitochondrial-Oxidative Stress Using Deep Convolutional Neural Network." Oxidative Medicine and Cellular Longevity 2022 (2022). (SCI) (IF=7.310)

Iqbal, Muhammad Shahid, et al."Recognition of mRNA N4 Acetylcytidine (ac4C) by Using Non-Deep vs. Deep Learning." Applied Sciences 12.3 (2022): 1344. (SCI) (IF=2.83)

Iqbal, Muhammad Shahid, Iftikhar Ahmad, Luo Bin, Suleman Khan, and Joel JPC Rodrigues. "Deeplearning recognition of diseased and normal cell representation."Transactions on Emerging Telecommunications Technologies: e4017. (SCI)(IF=3.310)

Muhammad Shahid Iqbal, Iftikhar Ahmad, Muhammad Asif, Sun-Hee-Kim, Raja Majid Mehmood, Drug Investigation Tool: Identify Effect of Drug on Cell Image by using Improved Correlation", Software: Practice and Experience., Aug 2020 (Accepted). (SCI)(IF =3.200)

Iqbal MS, Luo B, Mehmood R,Alrige MA, Alharbey R. Mitochondrial Organelle Movement Classification (Fission and Fusion) via Convolutional Neural Network Approach. IEEE Access. 2019 Jun28.(SCI) (IF =4.09) 

Iqbal, Muhammad Shahid, and BinLuo. "Prediction of educational institution using predictive analytic techniques [J]." Education and Information Technologies (2018):1-15. (SCI) (IF =3.666)

Iqbal, Muhammad Shahid, Saeed El-Ashram, Sajid Hussain, Tamoor Khan, Shujian Huang, Rashid Mehmood, and Bin Luo [J]. "Efficient cell classification of mitochondrial images by using deep learning." Journal of Optics: 1-10.

Iqbal, Muhammad Shahid, et al."Analysis of bioenergy by using linear regression." SN Applied Sciences 1.10 (2019): EI, ESCI

Hussain, W., Wang, B., Niu,Y.,Gao, Y., Wang, X., Sun, J., Zhan, Q., Cao, R., Zhou, Iqbal, MS. and Jie,X.,2019. Epileptic Seizure detection with Permutation Fuzzy Entropy using robust machine learning techniques. IEEE Access. (SCI) (IF =4.09)

Kausar, Samina, Muhammad Habib,  Muhammad Yasir Shabir, Ata Ullah, Huahu Xu, Rashid Mehmood, Rong fang Bie, andMuhammad Shahid Iqbal. "Secure and efficient data transfer using spreading and assimilation in MANET." Software: Practice and Experience. (SCI)(IF=3.666)

Asif, Muhammad, Wuyang Zhou, Qingping Yu, Saifullah Adnan, Md Sadek Ali, and Muhammad Shahid Iqbal."Jointly designed quasi-cyclic LDPC-coded cooperation with diversity combining at receiver." International Journal of Distributed Sensor Networks 16, no. 7 (2020): 1550147720938974.(SCI) (IF =1.938)

Rehman, Abdul, Zhang Deyuan,Imran Hussain, Muhammad Shahid Iqbal, Yang Yang, and Luan Jing dong."Prediction of Major Agricultural Fruits Production in Pakistan by Using an Econometric Analysis and Machine Learning Technique[J]." International Journal of Fruit Science 18, no. 4 (2018):445-461. (SCI) (IF =1.359)

Iqbal, M.S., Luo, B., Khan,T.,Mehmood, R. and Sadiq, M., 2018. Heterogeneous transfer learning techniquesfor machine learning [J]. Iran Journal of Computer Science, pp.1-16.

Iqbal, Muhammad Shahid,Muhammad Sidaq, Muhammad Shabbir, Abdul Rehman, Muhammad Sajad, and TamoorKhan. "Assessment of Inspection Tools with Standard, Management Review, Technical Review, Inspection and Walkthroughs[J]." International Journal of Computer Science and Information Security 14, no. 5 (2016):622.

Abbasi, R., Luo, B., Rehman,G.,Hassan, H., Iqbal, M.S. and Xu, L., 2018. A new multilevel reversible bit-planesdata hiding technique based on histogram shifting of efficient compressed domain. Vietnam Journal of Computer Science, pp.1-12.

Project Title: Lettuce Image Classification using Convolutional Neural Network

The aim of the project was to create a piece of computer visionsoftware with the long-term goal of automated lettuce harvesting, funded by G’sGlobal Growers. Testing accuracies obtained were roughly 97.9% on 500 testimages of lettuce obtained from the field. 

Iqbal, Muhammad Shahid, et al. "Cell Recognition of Microscopy Images of TPEF (Two Photon Excited Florescence) Probes[J]." Procedia Computer Science 147 (2019):77-83. EI

Kausar, Samina, Rashid Mehmood, Muhammad Shahid Iqbal, Rongfang Bie, Shujaat Ali, and Yasir Shabir."Density peaks-based clustering for single-cell interpretation via multi kernel learning [J]." Procedia Computer Science 147 (2019):71-76. EI

Kausar, Samina, Xu Huahu, Rashid Mehmood, and Muhammad Shahid Iqbal. "Diffusion Kernel based Fast Adaptive Clustering of Single Cell RNA-seq Data." In Proceedings of the 2019 11th International Conference on Bioinformatics and Biomedical Technology, pp. 86-93. ACM, 2019. EI

Kabir, Asif, Edvin J. Kitindi, Gohar Rehman, Faisal Bin Ubaid, and M. Shahid Iqbal. "Economical and sustainable power solution for remote cellular network sites through renewable energy." In 2017 IEEE 2ndInformation Technology, Networking, Electronic and Automation Control Conference (ITNEC), pp. 1067-1072. IEEE,2017. EI

Waqar, Hussain, Jie Xiang, Mengni Zhou, Ting Hu, Bilal Ahmed, Syed Habib Shapor, M. Shahid Iqbal, and M.Raheel. "Towards classifying epileptic seizures using entropy variants." In 2019 IEEE Fifth International Conference on Big Data Computing Service and Applications(Big Data Service), pp. 296-300. IEEE, 2019. EI

Kausar, Samina, Xu Huahu, Muhammad Shahid Iqbal, Zhu Wenhao, Muhammad Yasir Shabir, and Muhammad Raheel."Faculty Prediction of Pakistani Institutions by using Convolutional Neural Network (CNN)."In Proceedings of the 2019 International Conference on Modern Educational Technology, pp. 39-44. 2019. EI

Khan, Tamoor, Jiangtao Qiu, Muhammad Asim Ali Qureshi, Muhammad Shahid Iqbal, Rashid Mehmood, and Waqar Hussain. "Agricultural Fruit Prediction Using Deep Neural Networks." Procedia Computer Science 174 (2020): 72-78. EI

 Book, Chapter: Iqbal, M. S., Ahmad, I., Khan, T., Khan, S.,Ahmad, M., & Wang, L. (2021).Recent Advances of Deep Learning in Biology. In Deep Learning for Unmanned Systems (pp. 709-732). Springer, Cham.

 Book, Chapter: Artificial intelligence for Robotics and Autonomous Systems, Deep learning and robotics, surgical robot applications (Accepted 2022)