Mr. Ghazi Abbas | Financial Engineering | Research Excellence Award

Dalian Uiversity of Technology | China

Ghazi Abbas is a researcher specializing in machine learning applications in finance and economics, with a particular focus on predicting default risk and financial risk management. His work explores interpretable hybrid stacking models for multi-class loan default prediction, contributing to data-driven decision-making in financial systems. His research is recognized in international journals, accumulating citations across Google Scholar and Scopus, reflecting measurable scholarly impact, with a current h-index of 1 and total citations of 8. Ghazi’s contributions highlight the integration of advanced computational techniques into economic modeling, demonstrating strong potential for innovation in financial risk prediction and management.

Citation Metrics (Google Scholar)

Citations 8

i10-index 0

h-index 1

🟦 Citations 🟥 i10-index 🟩 h-index

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Featured Publications

Consensus-Driven Feature Selection for Transparent and Robust Loan Default Prediction

– Scientific Reports, 2025

From Binary Scores to Risk Tiers: An Interpretable Hybrid Stacking Model for Multi-Class Loan Default Prediction

– Systems, 2026

Exit Without Choice: Interpretable Machine Learning Unlocks the Structural Drivers of Smallholder Dispossession in Pakistan

– Agricultural and Food Economics, 2026

Dr. Naveed khan | Finance | Research Excellence Award

Director | Shandong University | China

Dr. Naveed Khan is a finance and economics researcher whose work spans banking regulation, fiscal policy, public debt, capital markets, energy economics, and environmental sustainability. His research integrates econometric and machine-learning approaches to examine financial performance, governance, debt dynamics, green finance, and energy–growth–emissions linkages across developed and emerging economies. He has published in leading SSCI and ABS-ranked journals, with several Q1 articles under review or forthcoming. According to Scopus and Google Scholar, his research has received around 165 citations, with 5 indexed documents and an h-index of 2, reflecting growing international scholarly impact.

Citation Metrics (Scopus)

200

150

100

Citations
165

Documents
5

h-index
2

🟦 Citations 🟥 Documents 🟩 h-index