3 papers
cs.AI2026
TO-Agents: A Multi-Agent AI Pipeline for Preference-Guided Topology Optimization
Isabella A. Stewart, Hongrui Chen, Faez Ahmed
Topology optimization can generate efficient structures, but designers often must manually translate qualitative intent, such as desired visual style, product experience, or manufa…
cs.AI2026
GraphAgents: Knowledge Graph-Guided Agentic AI for Cross-Domain Materials Design
Isabella A. Stewart, Tarjei Paule Hage, Yu-Chuan Hsu +1
Large Language Models (LLMs) promise to accelerate discovery by reasoning across the expanding scientific landscape. Yet, the challenge is no longer access to information but conne…
cs.AI2026
Higher-Order Knowledge Representations for Agentic Scientific Reasoning
Isabella A. Stewart, Markus J. Buehler
Scientific inquiry requires systems-level reasoning that integrates heterogeneous experimental data, cross-domain knowledge, and mechanistic evidence into coherent explanations. Wh…