Mr. Shafiul Alom Ahmed
Assistant Professor
- Faculty of Engineering and Technology
Assistant Professor
Name: | Specialization: |
---|---|
Mr. Shafiul Alom Ahmed | Data Mining, Data Structure, Algorithms |
M.Sc in Computer Science | Gauhati University | 2012 |
M.Tech in Information Technology | Tezpur University | 2014 |
Ph.D(Pursuing) | Tezpur University | Thesis Submitted |
Period | Designation | Institute |
Nov-2021 to till date | Assistant Professor | Department of CSE(iNurture), Assam down town University |
Apr-2021 to Oct-2021 | PGT-CS | Kendriya Vidyalaya-4, Tezpur University |
Jan-2015 to June-2019 | Teaching Assistant | Department of CSE, Tezpur University |
Jul-2015 to Jun-2016 | Faculty (Part Time) | DOEACC Training Program, Tezpur University |
JOURNAL | |
1 | Ahmed S. A. & Nath B. "Identification of adverse disease agents and risk analysis using frequent pattern mining." Information Sciences 576, 609-641, 2021. Indexing: SCI, SCOPUS, Web of Science, Impact Factor: 6.795 |
2 | Ahmed S. A. & Nath B. “ISSP-tree: An improved fast algorithm for constructing a complete prefix tree using single database scan”, Expert Systems with Applications, 115603, 2021. Indexing: SCIE,Web of Science, SCOPUS, Impact Factor: 6.954. |
3 | Ahmed, S. A. & Nath, B. “Is single scan based restructuring always a suitable approach to handle incremental frequent pattern mining?" Journal of Computer Science 17 (3), 205-220, 2021. Indexing: SCOPUS, Impact Score: .67. |
Conference/Book Chapter | |
1 | Ahmed, S. A. & Nath, B. & A Talukdar, SbFP-growth: A Step to Removethe Bottleneck of FP-tree, Recent Developments in Machine Learning and Data Analytics,285–296,Springer 2019. |
2 | Ahmed, S. A. & Nath, B. “A survey on fp-tree based incremental frequent pattern mining.” In International Conference on Biologically Inspired Techniques in Many-Criteria Decision Making. 203–210, Springer, 2019. |
3 | Ahmed, S. A. & Nath, B. “Modified fp-growth: An efficient frequent pattern mining approach from fp-tree.” In International Conference on Pattern Recognition and Machine Intelligence. 47–55, Springer, 2019. |