Computational materials scientist developing AI-guided, first-principles, and exascale workflows for materials discovery.
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I am a Scientist I at Ames National Laboratory. My research connects AI/ML-assisted materials discovery, first-principles calculations, magnetic materials, rare-earth and rare-earth-free compounds, machine-learning interatomic potentials, and large-scale electronic-structure workflows.
For the complete academic profile, selected publications, scientific highlights, databases, and contact information, please visit:
- AI/ML-accelerated discovery of functional materials and experimentally relevant candidates.
- Rare-earth-free and rare-earth magnetic materials, with emphasis on magnetic anisotropy and phase stability.
- Synthesis-aware computational design using DFT, adaptive feedback, and machine-learning potentials.
- Scalable workflows for high-throughput and exascale first-principles calculations.
- Electronic-structure methodology for GW/BSE and low-dimensional materials.
- CMS project website: project website for machine-learning accelerated materials discovery.
- MLAMD database: coming soon.
I am especially interested in closed-loop materials discovery: generating candidates, learning from first-principles calculations, testing physical mechanisms, and using the results to guide the next round of search.