معرفی
Michael Adjeisah is a Research Fellow at Bournemouth University's CfACTs Research Centre, focused on interdisciplinary research in machine learning and artificial intelligence. His work spans computer vision, natural language processing, health informatics, and data science, with applications in cultural heritage technology, low-resource language processing, and medical systems.
Notable research areas include Adinkra symbol recognition using deep learning, graph neural networks for classification tasks, and sentiment analysis models leveraging attention mechanisms. He has contributed to advancements in neural machine translation for low-resource languages and blockchain-enabled privacy solutions for electronic health records.
Adjeisah's publications reflect a strong emphasis on practical applications of AI, with recent work addressing challenges in spoken digit recognition for Amharic and respiration-based biometric systems. His research often integrates multi-sensor fusion and data augmentation techniques to enhance model performance in real-world scenarios.
