0000-0002-4551-3470 Employment
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Publications (18)
- A family of large language models for materials research with insights into model adaptability in continued pretraining Save
- Evaluating large language model agents for automation of atomic force microscopy Save
- Autonomous Microscopy Experiments through Large Language Model Agents Save
- MaScQA: investigating materials science knowledge of large language models Save
- Reconstructing the materials tetrahedron: challenges in materials information extraction Save
- Accelerated design of chalcogenide glasses through interpretable machine learning for composition–property relationships Save
- Understanding the compositional control on electrical, mechanical, optical, and physical properties of inorganic glasses with interpretable machine learning Save
- MatSciBERT: A materials domain language model for text mining and information extraction Save
- Interpreting the optical properties of oxide glasses with machine learning and Shapely additive explanations Save
- Prediction of concrete strengths enabled by missing data imputation and interpretable machine learning Save