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Author

Amita Nandal

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Open access 2026

High-Performance Divide-and-conquer Algorithms: A Comprehensive Framework with Recursive Parallel Decomposition and Hardware-aware Optimization

A framework for parallel divide-and-conquer algorithms that separates the performance contributions of algorithmic structure from those of the underlying runtime, and introduces hardware-aware threshold selection for Intel’s hybrid P-core/E-core architecture.

Tetsurou Kizaki, D. C. Bogatinoska, Amita Nandal et al. · 0 citations
Open access Aug 2026

SHAP-guided Machine Learning for Interpretable Band Gap Prediction and Inverse Design in ABX₃ Perovskites

This work reports positive demonstration of inverse design of high confidence ABX3 candidates with 1.5–2.5 eV separations, such as the sub-optimized discovery of RbSnS3, which provides a scalable way towards rational discovery of perovskites.

Aldrin Manon, Rajiv Kumar Gill, vijay kumar et al. · 0 citations

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