Emmanuel Kwesi Baah is a lecturer in the Computer Science Department. He holds a BSc and MPhil. Degrees in Computer Science at Kwame Nkrumah University of Science and Technology (KNUST). He has a few publications and conference papers to his credit.
He holds Certificates in Machine Learning (Intro & Intermediate) from Kaggle, owned by Google, and a Certificate of Completion on Ethics responsibilities for peer reviewers from Elsevier’s Research Academy.
His research interests and areas span Computational Theory and Algorithm Design, Deep Learning applications for Computer Vision, Network Security and Business Intelligence, Programming Languages and Systems Programming, Software Design, and Engineering.
Emmanuel had been an Instructor for the Kwame Nkrumah University of Science and Technology, serving both as a Teaching Assistant and Graduate/Research Assistant, handling various courses such as Data Structures and Algorithms, Computer Architecture, Programming with C++, and Introduction to Computers. He also served as a Facilitator for the Institute of Distance Learning (IDL) KNUST, handling courses such as Fundamentals of Operating Systems, Internet Technologies, Enterprise Information Systems, Object-Oriented System Analysis and Design, and Ethical and Professional Practice in Information Technology. Emmanuel was a Full-time Lecturer at Christian Service University College (now Christian Service University), where he handled Programming with C++/Python/VB, Data Structures and Algorithms, Compiler Design, Computer Architecture and Organization, Web Applications, Software Engineering, Introduction to Artificial Intelligence among others. He is a reviewer for the Electronic Commerce Research and Application Journal(Elsevier).
He worked as a Software Consultant and a Programmer at Intelsoltech Company Limited, working on remote projects for some companies in the USA and Germany.
At LUG, he teaches Fundamentals of Computer Science, Software Design, Human-Computer Interaction, and Introduction to Programming modules.
Publications
- Kornyo, O., Asante, M., Opoku, R., Owusu-Agyemang, K., Tei Partey, B., Baah, E. K., & Boadu, N. (2023). Botnet attacks classification in AMI networks with recursive feature elimination (RFE) and machine learning algorithms. Computers & Security, 135, 103456. https://doi.org/10.1016/j.cose.2023.103456
- Takyi, K., Gidimadjor, J. A., Gyening, R. O. M., & Baah, E. K. (2022). Augmented Reality Indoor Navigation with Computer Vision. Available at SSRN: http://dx.doi.org/10.2139/ssrn.4180080
- Modey, P., Asamoah, D., Oppong, S. O., & Baah, E. K. (2022). Error Detection and Correction in Wireless Sensor Networks Using Enhanced Reverse Conversion Algorithm in Healthcare Delivery System. International Journal of Wireless and Microwave Technologies.12(5), 43-52. 10.5815/ijwmt.2022.05.05
- Baah, E. K., Hayfron-Acquah, J. Ben. & Asamoah D. (2021). A Novel Approach to Pre-Impact Measurement from Impact Investing Using Random Forest and Deep Neural Networks. International Journal of Computer Applications.183(20).
Conference Presentations
- Baah, E.K. et al. (2022). Enhancing Port Scans Attack Detection Using Principal Component Analysis and Machine Learning Algorithms. In: Ahene, E., Li, F. (eds) Frontiers in Cyber Security. FCS 2022. Communications in Computer and Information Science, vol 1726. Springer, Singapore. https://doi.org/10.1007/978-981-19-8445-7_8
- Oppong, S. O., Baah, E. K., Agbeko, M., & Terkper, J. N. (2021). Improved Botnet Attack Detection using Principal Component Analysis and Ensemble Voting Algorithm. 2021 ICCMA, International Conference on Computing, Computational Modelling and Application, 14th – 16th July 2021, Brest, France.
