Albert Dede
Full-time: Computer Engineering
Albert Dede is a PhD candidate in Computer Engineering at Kwame Nkrumah University of Science and Technology (KNUST). His research at the Responsible Artificial Intelligence Lab (RAIL-KNUST) focuses on advancing machine learning and computer vision. Specifically, he is working on representation learning, weakly supervised methods, and high-resolution image analysis for applications such as medical diagnostics. Albert’s work effectively bridges cutting-edge AI research with real-world challenges, as demonstrated by his authorship of peer-reviewed journal articles and his role as a reviewer for leading publications like Expert Systems with Applications. Albert is dedicated to education and mentorship. He brings his experience from his role as a Graduate Teaching Assistant at KNUST, where he taught courses in Communication Systems, Digital Signal Processing, and more. His teaching philosophy promotes project-based learning and encourages curiosity about emerging technologies. As an active member of professional organisations such as the IEEE and the Ghana Institution of Engineering (GhIE), he has participated in global AI initiatives, including Deep Learning Indaba and PyCon Africa. In addition to his academic pursuits, he contributes to open-source projects and collaborative research, motivated by a vision to make AI tools accessible and impactful. Learn more about his work at https://albert-dede.github.io.
- Computer Organization and Architecture
- Hardware and Systems Fundamentals
- Deep learning for Medical Applications
- Computer Vision and Representation Learning
- Photonics and Optical Computing
- Attn-DeCGAN: A Diversity-Enhanced CycleGAN With Attention for High-Fidelity Medical Image Translation. Engineering Reports (2025), 7(8), e70320. https://doi.org/10.1002/eng2.70320
- Wavelet-Enhanced Deformable Convolutional Network for Breast Cancer Classification in High-Resolution Histopathology Images. Applied Research (2025), 4(3), e70021. https://doi.org/10.1002/appl.70021
- Deep learning for efficient high-resolution image processing: A systematic review. Intelligent Systems With Applications (2025), 26, 200505. https://doi.org/10.1016/j.iswa.2025.200505
- Wavelet-Based Feature Extraction for Efficient High-Resolution Image Classification. Engineering Reports (2025), 7(2), e70027. https://doi.org/10.1002/eng2.70027
- Digital backpropagation based on binary logarithmic step size distribution for fibre non-linearity compensation. The Journal of Engineering, 2023(12), e12340. https://doi.org/10.1049/tje2.12340
- MPhil Computer Engineering, Kwame Nkrumah University of Science and Technology, Kumasi
- MA. Christian Ministry with Management, Christian Service University, Kumasi)
- BSc. Computer Engineering, Kwame Nkrumah University of Science and Technology, Kumasi
