Profile

Faculty and Department Affiliation

Faculty of Science and Engineering
Department of Computer Science and Engineering

Degrees and Universities Attended

MSc  in  Computer  Science  and  Engineering  from  Jahangirnagar  University
BSc  in  Computer  Science  and  Engineering  from  Jahangirnagar  University  
HSC  from  Barisal  Government  College,  Barisal
SSC  from  Balighona  S.M  High  School,  Jhalokathi

Short Introduction

Md. Shovon is currently working as a lecturer at the Department of Computer Science and Engineering at City University. He carried out his SSC from Balighona S.M High School, Jhalokathi and his HSC from Govt. Barisal College, Barisal. Further, he completed his undergraduate degree from the Department of Computer Science and Engineering (CSE) at Jahangirnagar University and his postgraduate degree from the Department of Computer Science and Engineering (CSE) at Jahangirnagar University. He received under graduate level scholarship from Jahangirnagar University for excellent academic success. He achieved Master’s research fellowship from National Science and Technology 2022-23 by Ministry of Information Communication Technology, Bangladesh. He participated in ICPC and IUPC hosted by renowned universities. His research domains are Data Mining, Machine Learning, Deep Learning, Natural Language processing & Artificial Intelligence.

Teaching experience

1 Lecturer,  Department  of  Computer  Science  and  Engineering,  City  University.
November  2024  –  Till  date.
2 Lecturer,  Department  of  Computer  Science  and  Engineering,  Daffodil  International  University
July  2022  –  June  2023.
3          Lecturer,  Department  of  Computer  Science  and  Engineering,  Bangladesh  University
January  2024  –  November  2024.

Research Interest

Machine  Learning.
Deep  Learning.
Natural  Language  Processing.
Data  Mining.
Image  Processing.

Publications

1.  Survey  on  Sentiment  Analysis  in  Bangla  Language.  Submitted  to  International  Journal  of  Automation,  AI  and  Machine  Learning.

2.  An  Explainable  AI-Driven  Machine  Learning  Approach  for  Maternal  Health  Risk  Analysis.  Accepted  to  International  Conference  on  Computer  and  Information  Technology  (ICCIT  2024).