Dr. Gulshan Saleem
Assistant Professor | Data Scientist | Researcher
Gulshan.saleem@ucp.edu.pk
0320-5087255, Ext#128
0320-5087255, Ext#128
Dr. Gulshan Saleem, a Ph.D. in Computer Science from COMSATS University Islamabad, Pakistan, specializes in anomaly detection and video analytics. With over 15 peer-reviewed publications, 400+ Google Scholar citations, and a cumulative impact factor exceeding 15, she holds 6 years’ experience and recognized expert in machine learning, data science, and AI. Currently serving as an Assistant Professor at the University of Central Punjab, she has extensive experience in teaching, research supervision, including organizing major events and leading strategic committees. Previously, she supervised multiple projects, authored grant-winning proposals, and managed institutional collaborations. Dr. Gulshan’s expertise spans data analysis, deep learning, information retrieval and AI frameworks, complemented by her role as a professional trainer. She is dedicated to advancing research, fostering student success, and bridging academia with industry.
| Ph.D | Computer Science | COMSATS University Islamabad, Lahore, Pakistan | 2019–2024 |
| M.S | Software Engineering | College of E&ME, NUST, Islamabad, Pakistan | 2014–2016 |
| B.S | Software Engineering | Fatima Jinnah Women University, Rawalpindi, Pakistan | 2010–2014 |
| Assistant Professor | University of Central Punjab | September, 2024–Present |
| Lecturer | Lahore Garrison University | October, 2022–September, 2024 |
| Research Officer | Video Analytics Lab, COMSATS University | 2019–2023 |
| 1 | Aslam, M. A., Wei, X., Ahmed, N., Saleem, G., Zhu, S., Xu, Y., & Hu, H. (2024). Tqp: An efficient video quality assessment framework for adaptive bitrate video streaming. IEEE Access. IEEE. |
| 2 | Saleem, G., Bajwa, U. I., Raza, R. H., & Zhang, F. (2024). Edge-Enhanced TempoFuseNet: A Two-Stream Framework for Intelligent Multiclass Video Anomaly Recognition in 5G and IoT Environments. Future Internet, 16(3), 83. MDPI. |
| 3 | Aslam, M. A., Ahmed, N., & Saleem, G. (2023). Vrl-iqa: Visual representation learning for image quality assessment. IEEE Access. IEEE. |
| 4 | Zaman, M. I., Bajwa, U. I., Saleem, G., & Raza, R. H. (2024). A robust deep networks based multi-object multi-camera tracking system for city scale traffic. Multimedia Tools and Applications, 83(6), 17163-17181. Springer US New York. |
| 5 | Saleem, G., Bajwa, U. I., & Raza, R. H. (n.d.). Surveilia: Anomaly identification using temporally localized surveillance videos. Available at SSRN 4308311. |
| 6 | Saleem, G., Bajwa, U. I., & Raza, R. H. (2022). Toward human activity recognition: a survey. Neural Computing and Applications. Springer Nature. |
| 7 | Saleem, G., Bajwa, U. I., Raza, R. H., Alqahtani, F. H., Tolba, A., & Xia, F. (2022). Efficient anomaly recognition using surveillance videos. PeerJ Computer Science, 8, e1117. PeerJ Inc. |
| 8 | Ahmad, N., Asif, H. M. S., Saleem, G., & Younus, M. U. (2022). Image quality assessment for foliar disease identification (AgroPath). arXiv preprint arXiv:2209.12443 |
| 9 | Ahmad, N., Younus, M. U., Anjum, M. R., Saleem, G., Gondal, Z. A., & Narejo, S. (2022). Efficient jpeg encoding using Bernoulli shift map for secure communication. Wireless Personal Communications, 125(4), 3405-3424. Springer US New York. |
| 10 | Maqsood, R., Bajwa, U. I., Saleem, G., Raza, R. H., & Anwar, M. W. (2021). Anomaly recognition from surveillance videos using 3D convolution neural network. Multimedia Tools and Applications, 80(12), 18693-18716. Springer US. |
| 11 | Maqsood, R., Bajwa, U. I., Saleem, G., Raza, R. H., & Anwar, M. W. (2021). Anomaly recognition from surveillance videos using 3D convolution neural network. Multimedia Tools and Applications. Springer. |
| 12 | Ahmad, N., Asif, H. M. S., Saleem, G., & Younus, M. U. (2021). Development of crop yield estimation model using soil and environmental parameters. arXiv preprint arXiv:2102.05755. |
| 13 | Ahmad, N., Asif, H. M. S., Saleem, G., Younus, M. U., Anwar, S., & Anjum, M. R. (2021). Leaf image-based plant disease identification using color and texture features. Wireless Personal Communications, 121(2), 1139-1168. Springer. |
| 14 | Saleem, G., Ahmed, N., & Qamar, U. (2021). Text Mining Through Label Induction Grouping Algorithm Based Method. arXiv preprint arXiv:2112.08486. |
| 15 | Saleem, G., Akhtar, M., Ahmed, N., & Qureshi, W. S. (2019). Automated analysis of visual leaf shape features for plant classification. Computers and Electronics in Agriculture, 157, 270-280. Elsevier. |
| 16 | Saleem, G., Ahmed, N., Khalid, H., Ma, S., Wang, H., Dong, Y., & Jian, F. (2017). Design and analysis of a robust compression friendly image encryption scheme. Algorithms, 8(2), 1-18. |
| 17 | Ahmed, N., Asif, H. M. S., & Saleem, G. (2016). A benchmark for performance evaluation and security assessment of image encryption schemes. International Journal of Computer Network and Information Security, 8(12), 18-29. Modern Education and Computer Science Press. |
| 18 | Saleem, G., Azam, F., Younus, M. U., Ahmed, N., & Yong, L. (2016). Quality assurance of web services: A systematic literature review. 2016 2nd IEEE International Conference on Computer and Communications (ICCC), 1391-1396. IEEE. |
| 19 | Maqbool, S., Ahmed, N., Saleem, G., & Iqbal, M. M. (2015). An efficient Hindi-Urdu transliteration system. SciInt (Lahore), 27(4), 4549-4553. |