Samuel Olawole Akande

Towards Self-Healing Machine Learning Systems: Continual Learning and Drift-Aware MLOps Pipelines for Supply Chain Operations

Emmanuel Ahaiwe, Samuel Olawole Akande & Susana Owusu-Ansah · Journal of Economics, Management and Trade · 2026

Supply-chain machine learning operates in inherently non-stationary settings, promotions, assortment churn, shocks, and sensor drift routinely shift data and labels, so static models degrade in accuracy, service levels, and latency. This review consolidates evidence on drift-awar...

Open access Research Article 10.9734/jemt/2026/v32i21390

Analytics of Third-Party Risk in U.S. Supply Chains: AI for Proactive Risk Scoring and Mitigation

Juliana Twum-Ampofoah, Samuel Olawole Akande, Daniel Kofi Yeboah & Attah Nnaemeka Melford · Journal of Engineering Research and Reports · 2025

U.S. supply chains face escalating third-party risks across cyber, financial, operational, and ESG domains as multi-tier networks, data heterogeneity, and regulatory scrutiny expand. This study aims to synthesise how AI/ML models and data pipelines produce decision-useful vendor...

Open access Research Article 10.9734/jerr/2025/v27i111693