Research Output

AI Sovereignty in the Global South: Power, Dependency, and Strategic Futures

AAAI 2026 Conference - Workshop Empowering Global South AI

Analyzes structural power asymmetries in AI development across the Global South, proposing multipolar policy frameworks involving the African Union, ASEAN, and South-South cooperation to counter digital dependency on foreign platforms.

Digital Sovereignty or Digital Serfdom? AI Strategies, Geopolitics, and the Quest for an Equitable Global South

EurIPS 2025 Conference - Workshop on Private AI Governance

Examines whether Global South countries are advancing toward digital sovereignty or drifting into digital serfdom. Uses a seven-dimensional framework and four case studies (Singapore, Vietnam, Kenya, and Syria) to reveal asymmetries in computing, talent, and regulation.

BAFNet: Deep contour-aware features for colorectal polyps segmentation

Expert Systems with Applications, October 2025

Introduces a boundary-aware feature fusion neural network for improved colorectal polyp segmentation through gating mechanisms that select high-quality contour features and enhance semantic accuracy.

Towards Culturally Attuned and Resource-Aware Foundation Models for East African Agriculture: A theoretical framework and research agenda

Deep Learning Indaba (DLI) 2025 Conference - Responsible AI Workshop

Oral presentation on theoretical framework for culturally attuned foundation models for East African agriculture. To be published in PMLR Conference Proceedings (Tentatively January 2026).

Prime Directives for Responsible AI for Africa: A Manifesto for Inclusive Technology

Data Science Africa (DSA) 2025, Ibadan University, Nigeria

We present a holistic framework for developing inclusive, ethical, and sustainable AI that addresses Africa's unique cultural, social, and economic contexts. We emphasize participatory design, data equity, and local empowerment to ensure AI benefits all African communities.

Rectifying the extremely weakened signals for cassava leaf disease detection

Zhang Jiayu, Baohua Zhang, Innocent Nyalala, Peter Mecha, Junlong Chen, Kunjie Chen, Junfeng Gao

Computers and Electronics in Agriculture, Volume 232, 2025

Developed an artificial intelligence approach to accurately detect cassava leaf diseases by enhancing weak signal patterns in agricultural imaging.

From Art to Algorithms: Co-Designing AI for Clove Grading with Zanzibar's Indigenous Experts

AFRICHI ACM Conference 2025

Proposes a socio-technical approach to modernizing Zanzibar's clove grading system. Validates a segmentation-first deep learning architecture, achieving 99.0% accuracy, while advocating for co-design with Indigenous experts to develop a low-cost mobile tool that fosters transparency and trust.