Author

Douglas L. Allaire

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Preprint Sep 2026

Portfolio-Based Constrained Multi-Objective Bayesian Optimization for Materials Design

Materials discovery and design campaigns can be formulated as constrained multi-objective Bayesian optimization (CMOBO) problems, within which each experimental decision negotiates between two coupled but competing goals: discovering feasible candidates and refining the underlying Pareto front. Here we recast acquisiti...

S. Sinha, Christofer Hardcastle, Robert Robinson et al. · 0 citations

#artificial intelligence Preprint Oct 2026

Agentic Resource Allocation for Batch Multi-Objective Bayesian Optimization in Autonomous Materials Discovery

The discovery and development of advanced materials is a challenging process constrained by the high time and monetary costs of synthesis, processing, and characterization. The underlying design spaces can be enormous, often with multiple competing objectives. Bayesian optimization (BO) provides a principled approach f...

Robert Robinson, S. P. Padhy, S. Sinha et al. · 0 citations

Jun 2026

Surrogate-Gated Generation and Foundation-Model Embeddings for Bayesian Materials Design

Closed-loop materials discovery iterates between proposing candidate structures and evaluating their properties, and property evaluation dominates the cost. In the generative variant, a learned prior proposes candidate crystals and a property oracle scores them; we ask whether a cheap probabilistic surrogate can triage...

Sk Md Ahnaf Akif Alvi, Jan Janssen, Danny Perez et al. · arXiv.org · 0 citations