
Henry Nunoo-Mensah is a Professional Engineer and a Lecturer in the Department of Computer Engineering, KNUST-Kumasi. He is the MSc. programmes co-ordinator for the World Bank funded KNUST Engineering Education Project (KEEP) at the College of Engineering, KNUST. He is also the Project Coordinator for Connected Devices (CoDe) Lab, a research lab within the Department of Computer Engineering. He is a Research Fellow at The Brew Hammond Energy Centre, College of Engineering -KNUST. He is interested in artificial intelligence, wireless sensor networks, algorithm design, and optimization research. His research is published in numerous reputable journals and also made presentations at conferences. He has also undertaken several consultancy services for numerous organizations, both local and international. He teaches courses at both the undergraduate and postgraduate levels
Data Science
1. Gadze, J. D., Bamfo-Asante, A. A, Agyemang, J. O, Nunoo-Mensah, H., and Opare, K. A-B. (2021): An Investigation into the Application of Deep Learning in the Detection and Mitigation of DDoS Attack on SDN Controllers. Technologies, 9, 14. https://doi.org/10.3390/technologies9010014
2. Acheampong F. A., Nunoo-Mensah H., Wenyu C. (2021): Transformer Models for Text-based Emotion Detection: A Review of BERT-based Approaches. Artificial Intelligence Review, 1-41. https://doi.org/10.1007/s10462-021-09958-2
3. Acheampong, F.A., Nunoo-Mensah, H., Wenyu, C. (2020): Comparative Analyses of BERT, RoBERTa, DistilBERT, and XLNet for Text-based Emotion Recognition, In 2020 17th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) (pp. 117-121). IEEE.
4. Acheampong, F.A., Nunoo-Mensah, H., Wenyu, C., Niyongabo, R. A. (2020): Recognizing Emotions from Texts using a BERT-based Approach, In 2020 17th International Computer Conference on Wavelet Active Media Technology and Information Processing (ICCWAMTIP) (pp. 62-66). IEEE.
5. Acheampong F. A, Wenyu C., and Nunoo-Mensah H. (2020) Text-based emotion detection: Advances, challenges and opportunities. Engineering Reports, 2(5):1–29. https://doi.org/10.1002/eng2.12189
6. Nunoo-Mensah H., Boateng K. O., and Gadze J. D. (2020): PSTRM: Privacy-aware Sociopsychological Trust and Reputation Models for Wireless Sensor Networks, Peer-to-Peer Network and Application, https://doi.org/10.1007/s12083-020-00906-5