Hussam Ali is a highly accomplished and dedicated individual with a remarkable academic and professional background in the field of computer science. His academic journey has been marked by significant achievements and contributions to the research community.

Hussam Ali obtained his Bachelor of Science in Computer Science (BSCS) degree in 2012, demonstrating his early commitment to the field. He then pursued higher education and earned his Master of Science (M.S.) degree from the University of Sargodha in 2014, showcasing his dedication to advancing his knowledge and skills.

His academic journey culminated in the successful completion of his Ph.D. degree from the COMSATS University Islamabad, Pakistan, in 2022. This accomplishment reflects his perseverance and dedication to conducting in-depth research and contributing to the academic community.

Currently serving as a Lecturer at the Department of Computer Science, University of Sargodha, Hussam Ali is actively engaged in both teaching and research. His role as an educator undoubtedly benefits aspiring computer scientists and contributes to the growth of the next generation in the field.

Furthermore, Hussam Ali's commitment to peer review is noteworthy. He has served as a reviewer for various prestigious journals, including IEEE Communications Surveys and Tutorials, Nature Scientific Reports, IEEE Transactions on Biomedical Circuits and Systems, IEEE/ACM Transactions on Computational Biology and Bioinformatics, and IEEE Transactions on Medical Imaging, among many others. His dedication to the peer review process is evidenced by his recognition as one of Publons' global Peer Review Award recipients for being among the top 1% of reviewers in the fields of Computer Science, Engineering, and Cross Field from 2017 to 2019. This recognition underscores his expertise and valuable contributions to the scholarly publishing ecosystem.

Hussam Ali's Ph.D. from COMSATS University Islamabad Wah Campus, Pakistan, further showcases his commitment to pursuing advanced knowledge and research excellence in computer science.

In summary, Hussam Ali's academic journey, professional roles, and contributions to the peer review process collectively demonstrate his exceptional dedication, expertise, and impact in the field of computer science. He is a valuable asset to both academia and the broader research community, and his future contributions are sure to be significant.

Load More

Research Journal




• Hussam Ali , 2022 , A shallow extraction of texture features for classification of abnormal video endoscopy frames. , Biomedical Signal Processing and Control , 77, IF: 5.76 , Web Link : https://www.sciencedirect.com/science/article/abs/pii/S1746809422002555
• Hussam Ali, Mussarat Yasmin, Muhammad Sharif, and Mubashir Husain Rehmani , 2020 , Color-based Template Selection for Detection of Gastric Abnormalities in Video Endoscopy , Biomedical Signal Processing and Control , Volume 56, IF: 3.7 , Web Link : https://www.sciencedirect.com/science/article/abs/pii/S1746809419302496
• Hussam Ali, Mussarat Yasmin, Muhammad Sharif, Mubashir Husain Rehmani, and Farhan Riaz , 2019 , A Survey of Feature Extraction and Fusion of Deep Learning for Detection of Abnormalities in Video Endoscopy of Gastrointestinal-tract , Artificial Intelligence Review , 53, IF: 5.7 , Web Link : https://link.springer.com/article/10.1007/s10462-019-09743-2
• Hussam Ali, Mussarat Yasmin, Muhammad Sharif, and Mubashir Husain Rehmani , 2018 , Computer Assisted Gastric Abnormalities Detection Using Hybrid Texture Descriptors for Chromoendoscopy Images , Computer Methods and Programs in Biomedicine , Volume 157, IF: 2.674 , Web Link : https://www.sciencedirect.com/science/article/abs/pii/S0169260717307575
• Hussam Ali, Muhammad Sharif, Mussarat Yasmin and Mubashir Husain Rehmani , 2017 , Computer-based classification of chromoendoscopy images using homogeneous texture descriptors , Computers in Biology and Medicine , 88, IF: 2.115 , Web Link : https://doi.org/10.1016/j.compbiomed.2017.07.002
• Hussam Ali, Muhammad IkramUllah Lali, M. Z. Nawazb, Muhammad Sharif and B. A. Saleem , 2017 , Symptom Based Automated Detection of Citrus Diseases Using Color Histogram and Textural Descriptors , Journal of Computers and Electronics in Agriculture , Volume 138, IF: 2.475 , Web Link : https://doi.org/10.1016/j.compag.2017.04.008
• Javeria Amin, Muhammad Sharif, Mussarat Yasmin, Hussam Ali and Steven Lawrence Fernandes , 2017 , A method for the detection and classification of diabetic retinopathy using structural predictors of bright lesions , Journal of Computational Science , Volume 19, IF: 1.925 , Web Link : https://doi.org/10.1016/j.jocs.2017.01.002

Load More