A record of ongoing research. Each entry describes the research problem, methodology, and current stage — grouped by the kind of work it represents.
From ideas to models
Progress begins when curiosity is translated into rigorous inquiry.
Co-authored research manuscripts and an ongoing M.Sc. thesis.
A resilient multi-echelon FMCG supply-chain network design model under supplier and warehouse disruptions, formulated using two-stage stochastic mixed-integer linear programming.
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A game-theoretic study of AI-powered chatbot adoption in e-commerce supply chains, focusing on consumer engagement, channel dynamics, strategic interactions, and equilibrium outcomes under AI-driven service innovation.
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An ongoing study of hypergraph neural networks and graph-based learning methods for modelling higher-order relationships in biomedical data.
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Self-directed projects with verified, reproducible results.
An interpretable, learning-augmented approach to last-mile delivery routing that combines operations research with interpretable machine learning and hierarchical zone-preference modelling, evaluated on real Amazon last-mile delivery routes using the official challenge scoring.
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A quasi-causal analysis of how dispatch-deadline breaches relate to late-delivery risk in e-commerce, using augmented inverse probability weighting with five-fold cross-fitting on real Olist order data.
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