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Kazi Islam

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Articles

An Explainable Machine Learning Model for Credit Risk Prediction Evidence from Commercial Banks in Bangladesh

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By Kazi Islam
| Scientific Research Publishing (SCIRP)
1. Introduction In today’s data-driven financial environment, credit risk management has become a fundamental concern for banking institutions worldwide, as it directly affects financial stability, profitability, and overall risk control (Chen & Guestrin, 2016). In the context of commercial banking, credit risk prediction is not only a technical problem but also a major business challenge.
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REVI-twin: an integrated AI-driven methodology for creating digital twin of residential electric vehicle infrastructure

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By Aparna Kishore, Kazi Islam, Madhav Marathe
| Nature Verified
Abstract Integrating electric vehicles (EVs) into homes and the electrical grid creates complex dynamics that traditional planning tools struggle to address. Accurately estimating residential EV charging demand typically requires resource-intensive agent-based simulations reliant on substantial input data, limiting scalability. We present REVI-Twin, an AI-driven digital twin of residential EV infrastructure that scales without computationally-intensive simulations.
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Computer Science > Computation and Language

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By Kazi Islam, Sadiul Arefin, Farig Yousuf Sadeque
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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