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Sponsored AI Networking Cookbook: Practical recipes for AI-assisted network automation and development AI Networking Cookbook: Practical recipes for AI-assisted network automation and development

Author

Aswin Karkadakattil

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3 papers indexed here

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Oct 2026

Physics-Informed Explainable Hybrid Machine Learning and True Pareto-Optimal Inverse Design for Strength–Conductivity Optimization of High-Performance Cu–Cr–X Copper Alloys

High-performance Cu–Cr–X copper alloys face an inherent trade-off between mechanical strength and electrical conductivity. This study develops a physics-informed, interpretable machine-learning framework for their optimization and inverse design. A literature-derived dataset of 3017 experimental records was compiled,...

Aswin Karkadakattil · 0 citations
Open access 2026

Physics-Guided Explainable Surrogate Framework for Topology-Aware Local Strain Prediction in Defect-Rich Additively Manufactured Materials

Predicting defect-driven strain localization in additively manufactured materials remains challenging because experimental datasets are often limited, expensive to generate, and characterized by complex defect topologies. Conventional machine learning models can provide accurate predictions but often lack physical inte...

Aswin Karkadakattil · 0 citations
Open access Sep 2026

Physics-Informed Digital Twin for Robust Inverse Parameter Identification under Sparse and Noisy Measurements

This work provides a comprehensive reliability-oriented evaluation by integrating optimization robustness, structural identifiability, uncertainty quantification, comparative benchmarking, and multi-noise validation within a single physics-informed digital twin framework, improving the reliability and interpretability...

Aswin Karkadakattil · 0 citations

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