The Faculty of Computer Science and Information Technology at the University of Chenab is a leading academic institution dedicated to imparting high-quality education in the field of computer science and information technology. With an exceptional faculty, state-of-the-art infrastructure, and a forward-thinking curriculum, the faculty provides an unparalleled learning experience to its students.
The faculty offers undergraduate and graduate degree programs in software engineering, computer science, and data science. These programs are designed to prepare students to become leaders in the rapidly evolving world of technology. The faculty has a strong emphasis on practical learning, and students are given ample opportunities to apply their skills through internships, projects, and industry partnerships.
The faculty is committed to providing a stimulating environment that encourages innovation and creativity. The faculty members are highly qualified and experienced, and they bring their real-world knowledge and experience to the classroom. They also actively engage in research and scholarship to advance the field of computer science and information technology.
The Faculty of Computer Science and Information Technology at the University of Chenab is dedicated to producing well-rounded graduates who are not only technically proficient but also have strong communication, problem-solving, and critical thinking skills. With its strong focus on practical learning, industry partnerships, and research, the faculty is an excellent choice for students who want to pursue a career in computer science and information technology.
To be an international partner in computing education, research and development with our graduates impacting the society as computing professionals and entrepreneurs demonstrating professional integrity and leadership.
- To produce best quality Computer Science & IT professionals and researchers by providing state-of-the-art training, hands on experience, and healthy research environment.
- To collaborate with industry and academia around the globe for achieving quality technical education and excellence in research through active participation of all the stakeholders.
- To promote academic growth by establishing Center of Excellences and offering inter-disciplinary postgraduate and doctoral programs.
- To establish and maintain an effective operational environment and deliver quality, prompt, cost effective and reliable technology services to the society as well as compliment the local and global economic goals.
Ashraf, Z., Mahmood, Z., & Iqbal, M. (2023). Lightweight Privacy-Preserving Remote User Authentication and Key Agreement Protocol for Next-Generation IoT-Based Smart Healthcare. Future Internet, 15(12), 386.
Ashraf, Z., Sohail, A., & Yousaf, M. (2023). Lightweight and authentic symmetric session key cryptosystem for client–server mobile communication. The Journal of Supercomputing, 1-25.
Ashraf, Z., Sohail, A., & Yousaf, M. (2023). Robust and lightweight symmetric key exchange algorithm for next-generation IoE. Internet of Things, 22, 100703.
Ashraf, Z., Sohail, A., Latif, S. A., Pitafi, A. H., & Malik, M. Y. (2023). Challenges and Mitigation Strategies for Transition from IPv4 Network to Virtualized Next-Generation IPv6 Network. Int. Arab J. Inf. Technol., 20(1), 78-91.
Butt, U. M., Arif, R., Letchmunan, S., Malik, B. H., & Butt, M. A. (2023). Feature Enhanced Stacked Auto Encoder for Diseases Detection in Brain MRI. Computers, Materials & Continua, 76(2).
Ikram, A., Butt, M. A., & Tariq, I. (2023). Comparative Analysis of Regression Algorithms used to Predict the Sales of Big Marts. Journal of Innovative Computing and Emerging Technologies, 3(1).
Butt, M. A., Danjuma, S., Ilyas, M. S. B., Butt, U. M., Shahid, M., & Tariq, I. (2023). Demand Prediction on Bike Sharing Data Using Regression Analysis Approach. Journal of Innovative Computing and Emerging Technologies, 3(1).
Butt, U. M., Ullah, H. A., Letchmunan, S., Tariq, I., Hassan, F. H., & Koh, T. W. (2023). Leveraging Transfer Learning for Spatio-Temporal Human Activity Recognition from Video Sequences. Computers, Materials & Continua, 74(3).
Butt, U. M., Letchmunan, S., Hassan, F. H., & Koh, T. W. (2022). Hybrid of deep learning and exponential smoothing for enhancing crime forecasting accuracy. Plos one, 17(9), e0274172.
Baig, R., Rehman, A., Almuhaimeed, A., Alzahrani, A., & Rauf, H. T. (2022). Detecting malignant leukemia cells using microscopic blood smear images: a deep learning approach. Applied Sciences, 12(13), 6317.
Fatima, M., Rextin, A., Nasim, M., & Yusuf, O. (2022, October). Digital Information Seeking and Sharing Behaviour During the COVID-19 Pandemic in Pakistan. In Multidisciplinary International Symposium on Disinformation in Open Online Media (pp. 44-62). Cham: Springer International Publishing.
Department of computer science has built strong linkage with industry and signed various MOUs with different software houses for jobs and internships.
Recently the University of Chenab has signed MOUs with following software houses.
- Techno Verse
- Twin Spider
- Dev Valley
- Cipher Coders
- Soft Pin
- Huawei ICT Academy
- Gujrat Chamber of Commerce and Industries