Registration services will be closed on Monday, Dec 15th at 11:59 PM and will reopen on Wednesday, Dec 17th, at 12:01 AM. This pause is necessary to ensure data integrity during Canvas roster maintenance.
Department of Computer Science
Blessing Ojeme
Office: McMechen Hall Room 621
blessing.ojeme@morgan.edu
Dr. Blessing Ojeme is an Assistant Professor of Computer Science and a faculty member at the Center for Equitable Artificial Intelligence and Machine Learning Systems (CEAMLS) at Morgan State University, where he brings deep expertise in explainable artificial intelligence, data science, computer vision, image processing, and algorithmic robustness. Dr. Ojeme's teaching and research agenda, notable for its technical sophistication and social relevance, are driven by the question of how computing technologies can better solve real-world problems.
Dr. Ojeme’s academic trajectory reflects both depth and breadth. Prior to joining Morgan State in 2023, Dr. Ojeme served as a postdoctoral research associate in the Department of Computer Science at the University of Georgia, Athens, where he contributed to high-impact projects and collaborated across disciplinary boundaries. He earned his PhD in Computer Science from the University of Cape Town, South Africa, following a Bachelor’s and Master’s degree from the University of Benin, Nigeria.
At Morgan State University, he teaches artificial intelligence, machine learning, Python programming, data structures, design and analysis of algorithms, and software engineering at both undergraduate and graduate levels. A strong advocate for interdisciplinary collaboration and STEM education, Dr. Ojeme remains committed to empowering the next generation of innovators with technical tools and critical thinking through impactful teaching and research, and mentorship.
Dr. Ojeme’s active participation in CEAMLS further amplifies his commitment to inclusive innovation. Through CEAMLS, he engages with pressing equity challenges in AI, positioning his research to directly inform and improve public systems and safety-critical applications. His interest in explainable artificial intelligence, data science, computer vision, image processing, and algorithmic robustness demonstrates the critical alignment between technical excellence, scholarly rigor, and ethical responsibility.