Personal information

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Biography

Prof. S.A. Arekete hails from Igbotu, Ondo State, Nigeria. He teaches Computer Science in the Department of Computer Science of Redeemer's University, Ogun State, Nigeria. His current research interest is mobile agents and artificial intelligence. He had lectured at the Federal University of Technology, Akure and Bells University of Technology, Ota. He also had rich experience in the industry where he was a Data Processing Manager at Research & Marketing Services, Lagos, Head, Data Engineering Unit, Infosense Pty, Cape Town, South Africa and Assistant General Manager (AGM) IT & Analysis Division, Market Research Consultancy Ltd, Lagos between 1996 and 2005.

Activities

Employment (4)

Redeemer's University: Ede, Osun, NG

2017-10-01 to present | Professor (Computer Science Department)
Employment
Source: Self-asserted source
Samson Arekete

Redeemer's University: Redemption City, Ogun, NG

2014-01-29 to present | Senior Lecturer (Computer Science)
Employment
Source: Self-asserted source
Samson Arekete

Redeemer's University: Redemption City, Ogun, NG

2007-11-01 to 2014-01-28 | Lectuer I (Mathematical Sciences Department)
Employment
Source: Self-asserted source
Samson Arekete

Bells University of Technology: Ota, Ogun, NG

2005-10-02 to 2007-10-31 | Lecturer I (Computer Science)
Employment
Source: Self-asserted source
Samson Arekete

Education and qualifications (3)

Federal University of Technology Akure: Akure, Ondo, NG

2007-04-27 to 2013-05-31 | Ph.D Computer Science (Computer Science)
Education
Source: Self-asserted source
Samson Arekete

Federal University of Technology Akure: Akure, Ondo, NG

1991-02-01 to 1995-08-31 | M.Tech. Computer Science (Computer Science)
Education
Source: Self-asserted source
Samson Arekete

Federal University of Technology Akure: Akure, Ondo, NG

1982-11-22 to 1987-07-24 | B.Tech. Engineering Physics (Electronics) (Physics)
Education
Source: Self-asserted source
Samson Arekete

Works (1)

Modeling a deep transfer learning framework for the classification of COVID-19 radiology dataset

PeerJ Computer Science
2021-08-03 | Journal article
Contributors: Michael Adebisi Fayemiwo; Toluwase Ayobami Olowookere; Samson Afolabi Arekete; Adewale Opeoluwa Ogunde; Mba Obasi Odim; Bosede Oyenike Oguntunde; Oluwabunmi Omobolanle Olaniyan; Theresa Omolayo Ojewumi; Idowu Sunday Oyetade; Ademola Adegoke Aremu et al.
Source: check_circle
Crossref