Benjamin Kommey
Kwame Nkrumah University of Science and Technology
- Associate Professor, Kwame Nkrumah University of Science and Technology, since 2023per ORCID
Publishing since 2015, latest 2026
Prof. Benjamin Kommey is an associate Professor at the Faculty of Electrical and Computer Engineering, Kwame Nkrumah University of Science and Technology, KNUST and a European certified professional engineer ((EUR ING) FEANI register number 33677, (Dipl.-Ing.) VDE no. 6209053) and a member of the German Association of Electrical and Electronics Engineers (VDE/VDI Berlin/ Brandenburg). He had both his undergraduate and postgraduate studies in Germany, where he studied… More on ORCID
- Electrical and Electronic Engineering
- Control and Systems Engineering
- Information Systems
- Computer Networks and Communications
- Media Technology
- Computer Vision and Pattern Recognition
In their own words
- Embedded Systems
- Intelligent Systems
- Electronics
- Robotics
- Publications
- 722015–2026
- Citations
- 348to those papers
- h-index
- 10i10-index 10
- Field-weighted impact
- 0.731.00 is the world average
- World top 10%
- 5%3 of 62 scored papers
- Open access
- 100%62 of the 62 whose access is recorded
8 other works — preprints, datasets and the like — are listed but not counted.
Google Scholar shows 491 citations, h-index 12 and i10-index 15 (484 citations and h-index 12 since 2021), as of October 10, 2026. It also counts theses, books and web pages, so it runs higher.
By year
Papers, and the citations to them
Publications, left axisCitations to that year’s papers, right axis2026 still in progress
Citations received each year
Positions
- Associate Professor, Computer EngineeringKwame Nkrumah University of Science and Technologysince 2023
- Senior Lecturer, Computer EngineeringKwame Nkrumah University of Science and Technology2019–2023
- Lecturer, Computer EngineeringKwame Nkrumah University of Science and Technology2014–2019
Education
- Technische Universität Berlin
Honours, memberships and service
- FEANI
Publications
72 in all
- Residential Energy Demand‐Side Management Using Deep Learning Models: A Steady State Energy Disaggregation and Forecasting of Appliance Consumptions
2026The Journal of EngineeringJournalOpen accessCorresponding0 citations10.1049/tje2.70192
- Remaining Useful Lifetime Prediction of Distribution Transformer Using Dynamic Multi-Scale Attention-based CNN-LSTM