Dr Syed Arshad Ali

About

Dr. Syed Arshad Ali is working as an Assistant Professor in the Department of Computer Science and Applications at Sharda University with a passion for teaching and research, Dr. Arshad brings a wealth of expertise and knowledge to the field of computer science. He received his PhD degree in Computer Science from Jamia Millia Islamia, New Delhi. He received his Master of Computer Application (MCA) degree from Jamia Hamdard, New Delhi and Bachelor of Computer Application (BCA) degree from C.S.J.M. University, Kanpur. He has also qualified UGC, National Eligibility Test (NET) with JRF. In addition to journal articles and conference papers, his publications include book chapters and book reviews. He has also reviewed many research articles of reputed journals and conferences. In addition to Cloud Computing, Internet of Things, and Machine Learning, he is also interested in other areas of research.

Experience

• 4+ years 

Qualification

• BCA from CSJM University, Kanpur
• MCA from Jamia Hamdard, New Delhi
• UGC-NET JRF & SRF
• PhD (Computer Science) from Jamia Millia Islamia, New Delhi
   

Research

• SCI/ SCIE/ ESCI/ Scopus Articles- 03
• Book Chapter- 02
• International Conferences- 03 

List of Publications:

• S. A. Ali, S. Khan and M. Alam, "Resource-Aware Min-Min (RAMM) Algorithm for Resource Allocation in Cloud Computing Environment", International Journal of Recent Technology and Engineering, vol. 8, no. 3, pp. 1863-1870, 2019. DOI: 10.35940/ijrte.C5197.098319. (Scopus)
• Samiya Khan, Xiufeng Liu, Syed Arshad Ali, Mansaf Alam, ―Bivariate, cluster, and suitability analysis of NoSQL solutions for big graph applications, Advances in Computers ", Elsevier,2022, ISSN 0065-2458. https://doi.org/10.1016/bs.adcom.2021.09.006. (SCI Impact Factor 2.655)
• M Ansari, SA Ali, M Alam, “Internet of things (IoT) fusion with cloud computing: current research and future direction”, International Journal of Advanced Technology and Engineering Exploration, ACCENTS, 2022, ISSN 2394-5443, pp. 1812-1845 doi: http://dx.doi.org/10.19101/IJATEE.2021.876002 (Scopus) 
• S. A. Ali and M. Alam, "A relative study of task scheduling algorithms in cloud computing environment," 2016 2nd International Conference on Contemporary Computing and Informatics (IC3I), 2016, pp. 105-111, doi: 10.1109/IC3I.2016.7917943. (Scopus)
• S. A. Ali, M. Affan and M. Alam, "A Study of Efficient Energy Management Techniques for Cloud Computing Environment," 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence), 2019, pp. 13-18. doi: 10.1109/CONFLUENCE.2019.8776977. (Scopus)
• S. Khan, K. A. Shakil, S. Arshad Ali and M. Alam, "On Designing a Generic Framework for Big Data-as-a-Service," 2018 1st International Conference on Advanced Research in Engineering Sciences (ARES), 2018, pp. 1-5, doi: 10.1109/ARESX.2018.8723269. (Scopus)
• Ali, S.A., Ansari, M., Alam, M. (2020). ―Resource Management Techniques for Cloud-Based IoT Environment‖. Internet of Things (IoT). Springer, Cham. https://doi.org/10.1007/978-3-030-37468-6_4. (Scopus)
• Khan, S., Ali, S.A., Hasan, N., Shakil, K.A., Alam, M. (2019). Big Data Scientific Workflows in the Cloud: Challenges and Future Prospects. In: Das, H., Barik, R., Dubey, H., Roy, D. (eds) Cloud Computing for Geospatial Big Data Analytics. Studies in Big Data, vol 49. Springer, Cham. https://doi.org/10.1007/978-3-030-03359-0_1. (Scopus)
   

Area of Interest

• Cloud Computing
• Internet of Things (IoT)
• Machine Learning