News
Papers, talks, awards, and milestones — newest first.
Accelerating Quantum Materials Discovery Workshop
"Physics-based representations for data-efficient ML in MOF screening."
New paper in Molecular Systems Design & Engineering
Our work on 2D interaction-parameter histograms as a versatile nanoporous-material representation for ML prediction of adsorption is now an Advance Article.
New paper in Chemistry of Materials
Interactions of Common Synthesis Solvents with MOFs Studied via Free Energies of Solvation: Implications on Stability and Polymorph Selection.
Review out in Materials Horizons
"Machine learning to design metal–organic frameworks: progress and challenges from a data efficiency perspective."
JACS paper on fast ML prediction of MOF free energy
Highly accurate and fast prediction of MOF free energy via machine learning — with the MOFMinE database released openly.
Started postdoctoral position at the Toberer Group
Joined the Colorado School of Mines as a postdoctoral researcher, working on AI/ML for materials discovery and agentic orchestration for materials design.