activity
20232026
most citedGenerative Discovery of Novel Chemical Designs using Diffusion Modeling and Transformer Deep Neural Networks with Application to Deep Eutectic Solvents

50 citations · 59 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI2026★ 1 cited

Autonomous Agents Coordinating Distributed Discovery Through Emergent Artifact Exchange

Fiona Y. Wang, Lee Marom, Subhadeep Pal +4

We present ScienceClaw + Infinite, a framework for autonomous scientific investigation in which independent agents conduct research without central coordination, and any contributo…

cs.GR2026

Bioinspired123D: Generative 3D Modeling System for Bioinspired Structures

Rachel K. Luu, Markus J. Buehler

Generative AI has made rapid progress in text, image, and video synthesis, yet text-to-3D modeling for scientific design remains particularly challenging due to limited controllabi…

cs.LG2025

Generative Artificial Intelligence Extracts Structure-Function Relationships from Plants for New Materials

Rachel K. Luu, Jingyu Deng, Mohammed Shahrudin Ibrahim +4

Large language models (LLMs) have reshaped the research landscape by enabling new approaches to knowledge retrieval and creative ideation. Yet their application in discipline-speci…

cs.CL2024★ 5 cited

Fine-tuning large language models for domain adaptation: Exploration of training strategies, scaling, model merging and synergistic capabilities

Wei Lu, Rachel K. Luu, Markus J. Buehler

The advancement of Large Language Models (LLMs) for domain applications in fields such as materials science and engineering depends on the development of fine-tuning strategies tha…

cond-mat.mtrl-sci2023★ 3 cited

BioinspiredLLM: Conversational Large Language Model for the Mechanics of Biological and Bio-inspired Materials

Rachel K. Luu, Markus J. Buehler

The study of biological materials and bio-inspired materials science is well established; however, surprisingly little knowledge has been systematically translated to engineering s…

cond-mat.mtrl-sci2023★ 50 cited

Generative Discovery of Novel Chemical Designs using Diffusion Modeling and Transformer Deep Neural Networks with Application to Deep Eutectic Solvents

Rachel K. Luu, Marcin Wysokowski, Markus J. Buehler

We report a series of deep learning models to solve complex forward and inverse design problems in molecular modeling and design. Using both diffusion models inspired by nonequilib…