DR BENJAMIN ASUBAM WEYORI

DR BENJAMIN ASUBAM WEYORI

Biography

Dr Benjamin Asubam Weyori is currently a Senior Lecturer in the Department of Computer Science and Informatics at the University of Energy and Natural Resources (UENR) in Ghana. Benjamin has held the Acting Head position of the Department of Computer Science and Informatics since September 2017 to date. He was the coordinator of the same Department in the 2013/2014 academic year.

 

Benjamin has held several positions as Lecturer from  2011 to 2012 in the Faculty of Information, Communication, Science and Technology at the Catholic University College of Ghana (CUCG), Sunyani and a Senior Research Assistant in the Department of Computer Science at the University for Development Studies (UDS), Tamale from 2007-2010.

 

Benjamin holds a PhD in Computer Engineering, MPhil in Computer Engineering and a Bachelor of Science in Computer. His main research interest includes; Artificial Intelligence, Computer Visions (Image Processing), Machine Learning and Web Engineering.

 

RECENT PUBLICATIONS

  • Benjamin Asubam Weyori, Kwame Osei Boateng, Sampson Twumasi-Ankrah (2017): Efficient Novel Vector Median Filter Design for Impulse Noise Suppression in Color Images, International Journal of Innovative Computing, Information and Control (IJICIC), Volume 13, Number 6, pp. 1965-1980

 

  • Benjamin Asubam Weyori, Kwame Osei Boateng, Peter N. Amponsah, Paul K. Yeboah (2016): Design and Implementation of the Block Matching Hybrid Median Filter for Noise Removal in Color Images, International Journal of Innovative Computing, Information and Control (IJICIC), Volume 12, Number 6, pp. 1865-1879

 

  • Benjamin Asubam Weyori, Kwame Osei Boateng, Peter N. Amponsah, Paul K. Yeboah, Stephen Akobre (2016): Simulating the Effect of Noise and Distortions On The RGB Component Of Real World Color Images, International Journal of Innovative Computing, Information and Control (IJICIC), Volume 12, Number 6, pp. 1929 -1941.

 

  • Sheng Wang, Jianfeng Lu, Xingjian Gu, Benjamin A. Weyori, Jing-Yu Yang (2016): Unsupervised discriminant canonical correlation analysis based on spectral clustering. Neurocomputing, 171, pp 425-433.

 

QUALIFICATION

S/NO

NAME OF INSTITUTION

YEAR

 

DEGREE

1.

Kwame Nkrumah University of Science and Technology (KNUST)

2016

PhD in Computer Engineering

2

Kwame Nkrumah University of Science and Technology (KNUST)

2011

MPhil Computer Engineering

3.

University for Development Studies (UDS)

2006

BSc. Computer Science

 

RESEARCH INTEREST

Machine Learning, Artificial Intelligence, Computer Visions and Image Processing

 

POSITIONS

S/No.

POSITION

DURATION

1.

Acting Head, Computer Science & Informatics

Sept. 2017 – To Date

2.

Coordinator, School of Sciences Top-Up/Weekend Programme

February 2017 – To Date

3.

Graduate Programme Coordinator, Dept. Of Computer Science & Informatics

February 2017 – To Date

4.

Member, Promotion Policy Review Committee

July 2017 – To Date

5.

Chairman, Curriculum development committee (BSc. Computer Science)

Dec. 2012 – Jan. 2013

6.

Chairman, Curriculum development committee (BSc. Information Technology)

Oct. 2013 – Nov. 2013

7.

Chairman, Curriculum development committee (Diploma Computer Science)

May 2017 – June 2017

8.

Chairman, School of Sciences Sports committee

Sept. 2017

9.

Member, Curriculum development committee (MSc./MPhil./PhD Computer Science)

Jan. 2017 – March 2017

10.

First Patron, Computer Science and Information Technology Students Association (CISTSA)

Nov. 2013 – August 2014

11.

Coordinator of Programmes, Department of Computer Science and Informatics

Sept. 2013 – Sept. 2014

 

ASSOCIATIONS / AFFILIATIONS

  1. Member – Institute of Electrical & Electronics Engineers (IEEE)
  2. Member – IEEE Computer Society
  • Member – International Association of Engineers (IAENG)
  1. Member – American Computer Machinery (ACM)

RESEARCH PROJECTS

 

  1. Activity-Based Segmentation of the Human Brain Using an Improved Independent Component Analysis (On-going)

 

  1. Bayesian Modelling of the Human Brain Bayesian Modeling of fMRI data. (On-going)