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Independent Researcher specializing in Artificial Intelligence, Machine Learning, and Data Science.
Focus on transparent and trustworthy AI systems that advance real-world impact.
Expertise in:
Explainable AI (XAI): improving interpretability, trust, and accountability in ML models.
Agentic AI Systems: designing adaptive, multi-agent orchestration for robust decision-making.
Forecasting & Optimization: developing leakage-free pipelines applied to aviation, energy, retail, and healthcare.
Dedicated to bridging theory and practice , ensuring AI innovations are impactful, socially responsible, and aligned with national priorities.
π οΈ Featured Projects
Contributed to a vision-driven accessibility tool translating sign language into text.
Improved CNN pipeline for robustness across conditions.
Built a unified pipeline combining statistical and ML models.
Integrated SHAP, LIME, and Permutation Importance for transparent results.
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