Author

Jolene P. Reid

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Sep 2026

Enabling Data-Efficient Machine Learning through Multi-Target Training Set Design via Greedy Neighborhood Coverage

Machine learning is increasingly used to guide asymmetric catalysis, but each enantioselectivity measurement remains experimentally expensive. Prior work established that predictive accuracy in these datasets is dominated by reactions that are structurally similar to the target, motivating neighborhood-restricted mod...

Jakob A. Meckes, Jiang-Yi He, Jolene P. Reid · ACS Catalysis · 0 citations

Jul 2026

Underexplored Catalysts as General Structures: Application of Machine Learning Techniques for Reaction‐Specific Datasets

A bias‐aware machine learning workflow designed for small, uneven datasets to prioritize candidate general catalysts from limited historical data surfaced several high‐performing candidates, including a rarely studied imidazolidinone bearing a benzyl‐protected indole substituent.

Jiajing Li, Isaiah O. Betinol, Junshan Lai et al. · Angewandte Chemie · 0 citations

#artificial intelligence Preprint Aug 2026

MAIL: Memory-driven, Adaptive, Incremental, and Literature-grounded Framework for Hypothesis Generation in Chemistry

The proposed MAIL framework generates structurally coherent and mechanistically plausible hypotheses, achieves the highest MIOS and MPOS by more effectively recovering the central ideas and methodological elements of the historical target hypotheses, and obtains the highest overall expert-evaluation scores for scientif...

Mahdi Babaei, Xueshen Li, Yutao Kuang et al. · 0 citations