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Research Interests

Recent research:
Integrated across education and engineering domains, the researcher advances mathematics education through a rigorous, criterion-driven selection of error-classification frameworks for first-year engineering students, demonstrating the Newman model as the most effective for diagnostic and formative purposes via Analytic Hierarchy Process (AHP). Complementing this, the portfolio further develops predictive maintenance and performance optimization in diesel and automotive contexts by applying multivariate statistics, change-point detection, and response surface methodologies to lubricant analysis, oil viscosity, and fuel quality. The work consistently demonstrates how data-driven methods—PCA, BS change-point detection, RSM, and high-altitude field testing—enhance maintenance timing, engine efficiency, and emission outcomes. A unifying impact is the translation of complex analyses into actionable guidelines for educational instrument design and sustainable, cost-efficient vehicle operation in challenging environments, highlighting evidence-based criteria, reliability-focused maintenance, and operational optimization as core contributions to both pedagogy and engineering practice.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  1. SDG 11 - Sustainable Cities and Communities
    SDG 11 Sustainable Cities and Communities

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Collaborations and top research areas from the last five years

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