- Faculty of Computer Science and Information Technology
Faculty
Faculty of Computer Science and Information Technology
Undergraduate
4 years full-time
Postgraduate
2 years full-time
Faculty Overview
Departments
Faculty Overview
The Faculty of Computer Science and Information Technology at the University of Chenab is a leading academic institution. It plays a key role in imparting high-quality education in the field of computer science and information technology. The institution offers exceptional faculty, state-of-the-art infrastructure, and a forward-thinking curriculum. Meanwhile, the faculty provides a matchless learning experience to its students.
The faculty offers undergraduate and graduate degree programs in software engineering, computer science, and data science. These programs are available to prepare students to become leaders in the rapidly evolving world of technology. The faculty has a strong emphasis on practical learning. Additionally, students get ample opportunities to apply their skills through internships, projects, as well as industry partnerships.
Our Main Mission
The faculty is loyal to providing a stimulating environment that encourages innovation and creativity. The faculty members are highly professional, and they hence bring their real-world knowledge and experience to the classroom. Furthermore, 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, as well as critical thinking skills. The faculty comes with the strong focus on practical learning, industry partnerships, as well as research. Hence, this makes it an excellent choice for students who want to pursue a career in computer science and information technology.
Departments
Our vision is to be an international partner in computing education, research and development. Well, our graduates should be impacting society as computing professionals and entrepreneurs should highlight professional integrity and leadership.
Department works with a clear mission to provide the country with trained resources. High-tech products and services are available to exercise commercialization through incubation of high-tech companies.
- To produce best quality Computer Science & IT professionals and researchers by providing state-of-the-art training, hands on experience, and healthy research environment.
- 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 as well as offering inter-disciplinary postgraduate and doctoral programs.
- 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.
- Making world class technology available to undertake large and complex IT Projects in Pakistan
- Exercising commercialization through incubation of high tech companies.
Currently, the Department is offering the following undergraduate and postgraduate degree programs:
2024
Ejaz, S., Baig, R., Ashraf, Z., Alnfiai, M. M., Alnahari, M. M., & Alotaibi, R. M. (2024). A deep learning framework for the early detection of multi-retinal diseases. PLOS ONE, 19(7), e0307317.
Shaukat, F., Ejaz, N., Ashraf, Z., Alnfiai, M. M., Alnahari, M. M., & Alotaibi, R. M. (2024). GenVis: Visualizing Genre Detection in Movie Trailers for Enhanced Understanding. IEEE Access.
Ashraf, Z., Sohail, A., & Iqbal, M. (2024). Design and Implementation of Lightweight Certificateless Secure Communication Scheme on Industrial NFV-Based IPv6 Virtual Networks. Electronics, 13(13), 2649.
Mahmood, Z., Ashraf, Z., Iqbal, M., & Farooq, B. (2024). User-trust centric lightweight access control for smart IoT crowd sensing applications in healthcare systems. Personal and Ubiquitous Computing, 28(2), pp. 1-14.
2023
Ashraf, Z., Sohail, A., Hameed, A., Farhan, M., Alotaibi, F. A., & Alnfiai, M. M. (2023). Robust and Lightweight Remote User Authentication Mechanism for Next-Generation IoT-based Smart Home. IEEE Access 11, pp. 137899 – 137910
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).
2022
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.
Prince Sultan University, Riyadh, Saudi Arabia
King Saud University, Riyadh, Saudi Arabia
Taif University, Taif, Saudi Arabia
- University of Kotli, Kotli, Azad Jammu & Kashmir
- IQRA University, Islamabad Campus, Islamabad
- RIPHAH University, Islamabad Campus, Islamabad
- COMSATS University, Sahiwal Campus, Sahiwal
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.
- KMS Enterprise Solutions in Canada
- Techno Verse
- Twin Spider
- Dev Valley
- Cipher Coders
- Soft Pin
- Huawei ICT Academy
- Gujrat Chamber of Commerce and Industries
