4 citations · 4 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2026
A Generalizable Machine Learning Framework for Half-Heusler Thermoelectrics
Shoeb Athar, Adrien Mecibah, Philippe Jund
Machine learning (ML) has emerged as a powerful approach for accelerating the discovery of thermoelectric (TE) materials, yet many models suffer from limited generalizability. Here…
cond-mat.mtrl-sci2025★ 4 cited
Tackling dataset curation challenges towards reliable machine learning: a case study on thermoelectric materials
Shoeb Athar, Adrien Mecibah, Philippe Jund
Machine Learning (ML) driven discovery of novel and efficient thermoelectric (TE) materials warrants experimental TE datasets of high volume, diversity, and quality. While the larg…