PhD Computer Science - King Abdul Aziz University, KSA – 2019

MS Network System Engineering - University of Plymouth, UK - 2007

• Associate Professor – Institute for Art and Culture – September, 2024 – till date
• Assistant Professor – Grand Asian University Sialkot, Pakistan – 2022 -2024

September-2024

Dr. Sardar Usman is a seasoned professional with a rich academic background and over a decade of combined industrial and teaching expertise. Holding a BS in Computer Science from COMSATS Pakistan, a Masters in Network System Engineering from the University of Plymouth UK, and a PhD from King Abdul Aziz University, Saudi Arabia, his educational journey reflects a commitment to excellence in the field.

Dr. Usman has held significant positions in academia, having served as the Head of the Computer Science department at Leads University Lahore and currently holding the role of Assistant Professorin the department of CS & SE at Grand Asian University Sialkot. His diverse roles have allowed him to contribute significantly to the academic landscape while staying abreast of industry trends.

1. Usman, S.; Mehmood, R.; Katib, I.; Albeshri, A. Data Locality in High Performance Computing, Big Data, and Converged Systems: An Analysis of the Cutting Edge and a Future System Architecture. Electronics 2023, 12, 53. https://doi.org/10.3390/electronics12010053
2. Ahmed, M.; Usman, S.; Shah, N.A.; Ashraf, M.U.; Alghamdi, A.M.; Bahadded, A.A.; Almarhabi, K.A. AAQAL: A Machine Learning-Based Tool for Performance Optimization of Parallel SPMV Computations Using Block CSR. Appl. Sci. 2022, 12, 7073. https://doi.org/10.3390/app12147073.
3. M. Hasnain, I. Ghani, S. R. Jeong, M. F. Pasha, S. Usman et al., “Empirical analysis of software success rate forecasting during requirement engineering processes,” Computers, Materials & Continua, vol. 74, no.1, pp. 783–799, 2023. https://doi.org/10.32604/cmc.2023.030162. 4. Farwa Akram, Sardar Usman, Ashraf, M. U. (2022). Comparative Analysis of Machine Learning Techniques for Predicting Air Pollution. Lahore Garrison University Research Journal of Computer Science and Information Technology, 6(2), 40-54. https://doi.org/10.54692/lgurjcsit.2022.0602270.
4. Usman, Sardar & Mehmood, Rashid & Katib, Iyad & Albeshri, Aiiad. (2019). ZAKI+: A Machine Learning based Process Mapping Tool for SpMV Computations on Distributed Memory Architectures. IEEE Access. 7. 1-1. 10.1109/ACCESS.2019.2923565.
5. Usman, Sardar & Mehmood, Rashid & Katib, Iyad & Albeshri, Aiiad & Altowaijri, Saleh. (2019). ZAKI: A Smart

Method and Tool for Automatic Performance Optimization of Parallel SpMV Computations on Distributed Memory Machines. Mobile Networks and Applications. 10.1007/s11036-019-01318-3.

7. S. Usman., Mehmood R., Katib I. (2018) Big Data and HPC Convergence: The Cutting Edge and Outlook. In: Smart Societies, Infrastructure, Technologies and Applications. SCITA 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 224. Springer, Cham. DOI : 10.1007/978-3-319-94180-6 4
8. S. Usman, R. Mehmood, and I. Katib, “Big Data and HPC Convergence for Smart Infrastructures: A Review and Proposed Architecture” In Smart Infrastructure and Applications: Foundations for Smarter Cities and Societies. Springer (2020), DOI: 10.1007/978-3-030-13705-2_23.
9. Y.Arfat, S. Usman, R. Mehmood, and I. Katib, “ Big Data for Smart Infrastructures Design: Opportunities and Challenges”, In Smart Infrastructure and Applications: Foundations for Smarter Cities and Societies. Springer (2020),DOI: 10.1007/978-3-030-13705-2_20.
10. Y.Arfat, S. Usman, R. Mehmood, and A.Albeshri, “Big Data Tools, Technologies and Applications: A Survey”, In Smart Infrastructure and Applications: Foundations for Smarter Cities and Societies. Springer (2020), DOI: 10.1007/978-3-030-13705-2_19.
11. S. Usman, R. Mehmood, and I. Katib, “HPC & Big Data Convergence: The Cutting Edge & Outlook, Poster presented,” at the first Middle East meeting of the Intel Extreme Performance Users Group, IntelXPUG, King Abdullah University of Science and Technology (KAUST), 2018. https://epostersonline.com/ixpug-me2018/node/19.
12. S. Usman, Emad Alamoudi, “Parallel computing with MPI”, Tutorial Presented at HPC Saudi 2018, at KAU Jeddah, KSA, http://www.hpcsaudi.org/2018/wp-content/uploads/2018/04/20180314_Tutorial_Slides_SU_EA.pdf
13. S. Usman, Dong-Seong Kim, “Avionics Full Duplex Switched Ethernet/AFDX”, WIITC2014, pp. 141-145, Danang University of Science and Tech., Vietnam, 11-12 Feb. 2014.
14. M. Sajawal, S. Usman, H. Alshaikh, Asad.H, U. Ashraf. (2022). A Predictive Analysis of Retail Sales Forecasting using Machine Learning Techniques. Lahore Garrison University Research Journal of Computer Science and Information Technology, 6(04), 23-33. https://doi.org/10.54692/lgurjcsit.2022.0604399.
15. M hasnain; A Hussain; A Daud; I Ghani; S R Jeong; S Usman, Cyber Security Challenges in Blockchain based Social Media Networks: A Review. KSII. The 18th Asia Pacific International Conference on Information Science and Technology (APIC-IST) 2023.
16. Hanan Sharif, Sardar Usman, Muhammad Hasnain, Usman Ashraf. (2024). A Machine Learning Based Approach for the Detection of DDoS Attacks on Internet of Things Using CICDDoS2019 Dataset – PortMap. Lahore Garrison University Research Journal of Computer Science and Information Technology. 8(2), https://doi.org/10.54692/lgurjcsit.2024.082569 .
17. M. Hasnain, Sardar Usman, Potential of Large Language Models (LLMs) as Supplementary Tools for Historical Learning: Users’ Interaction and Knowledge Acquisition, Foundation University Journal of Engineering and Applied Sciences, Volume 4, Issue 2, pp. 60-66.
18. Sajid Khan; Hao Peng; Zhaoquan Gu; Sardar Usman; Namra Mukhtar, Integration of a Novel 3D Chaotic Map with ELSS and Novel Cross-Border Pixel Exchange Strategy for Secure Image Communication, Springer Journal of Complex & Intelligent Systems (CAIS), July, 2024. DOI: 10.1007/s40747-024-01568-z.
19. M. Hasnain, Sardar Usman, Ali Daud, COMPARISON OF DEEP LEARNING ALGORITHMS FOR RETAIL SALE FORECASTING, Jordanian Journal of Computers and Information Technology. ( Status : Submitted)
20. K. Sajid, Hao Peng; Zhaoquan Gu, Sardar Usman, Securing Digital Images: Leveraging 8-bit Conditional Logic Operation in Polynomial Chains with a Novel 2D Chaotic Map, Journal of Artificial Intelligence Review. (Status Submitted).
21. M. Hasnain, S. Usman. Rizwan.M, Fake Information Prevention Strategies on the COVID-19 Pandemic Incorporated with the ChatGPT Application, Springer SN Computer Science. (Status Submitted).
22. M.Hasnain, Sardar Usman, Ali Daud, ChatGPT-Assisted Energy Efficiency Enhancement for Blockchain Network Sustainability, KSII Transactions on Internet and Information Systems. (Status: Submitted).
23. Sardar Usman; Muhammad Ahmed; Ali Daud; Muhammad Hasnain, ELEGANTE: A Machine Learning based threads configuration tool for SpMV computation on shared memory architectures, IEEE Access. (Submitted).
24. M. Ahmed, Sardar Usman, M. Hasnain, K. Sajid, Posivox: Hope speech detection using social media discourse A Transfer learning approach, Springer Journal of Neural Computing and Applications (Status : Submitted).
25. M. Asghar, S Usman, M. Hasnain, M U. Ashraf, Analysing Energy Efficiency in HPC, Big Data, and Converged Systems, Exploring Cutting-Edge and Future energy aware green computing Architecture, International Journal of High Performance Computing Applications. (Status: Submitted).

PhD Scholarship. From King Abdul Aziz University, Saudi Arabia.

BS (CS)4 years Scholarship from COMSATS, Abbottabad Pakistan.