2 citations · 4 across the 11 of their papers we have counts for
11 papers
Overcoming Orchestration Bottlenecks at Exascale: A Decentralized, Policy-Driven Approach for Sim-AI Ensembles
Harikrishna Tummalapalli, Christine M. Simpson, Riccardo Balin +4
Scientific computing is increasingly shifting from monolithic applications to coupled simulation-AI workflows composed of highly heterogeneous tasks with diverse hardware, scale, a…
From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry
Aritra Roy, Kevin Shen, Andrew MacBride +350
Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broa…
Multi-Agent Orchestration for High-Throughput Materials Screening on a Leadership-Class System
Thang Duc Pham, Harikrishna Tummalapalli, Fakhrul Hasan Bhuiyan +5
The integration of Artificial Intelligence (AI) with High-Performance Computing (HPC) is transforming scientific workflows from human-directed pipelines into adaptive systems capab…
ChemGraph-XANES: An Agentic Framework for XANES Simulation and Curation
Vitor F. Grizzi, Thang Duc Pham, Luke N. Pretzie +3
Computational X-ray absorption near-edge structure (XANES) is widely used to interpret local coordination environments, oxidation states, and electronic structure, but large comput…
From Atomistic Models to Machine Learning: Predictive Design of Nanocarbons under Extreme Conditions
Xiaoli Yan, Millicent A. Firestone, Murat Keceli +2
The formation of technologically valuable nanocarbon structures under extreme conditions, such as those produced during high-explosive detonations, remains poorly understood but ho…
An Agentic Evaluation Framework for AI-Generated Scientific Code in PETSc
Hong Zhang, Barry Smith, Satish Balay +4
While LLMs have accelerated scientific code generation, comprehensively evaluating generated code remains challenging. Many benchmarks emphasize functional correctness or task comp…
Thermal Conductivity Limits of MoS and MoSe: Revisiting High-Order Anharmonic Lattice Dynamics with Machine Learning Potentials
Tugbey Kocabas, Murat Keceli, Tanju Gurel +2
Group-VI transition metal dichalcogenides (TMDs), MoS and MoSe, have emerged as prototypical low-dimensional systems with distinctive phononic and electronic properties, ma…
Red Teaming for Generative AI, Report on a Copyright-Focused Exercise Completed in an Academic Medical Center
James Wen, Sahil Nalawade, Zhiwei Liang +38
Background: Generative artificial intelligence (AI) deployment in academic medical settings raises copyright compliance concerns. Dana-Farber Cancer Institute implemented GPT4DFCI,…
ChemGraph: An Agentic Framework for Computational Chemistry Workflows
Thang D. Pham, Aditya Tanikanti, Murat Keçeli
Atomistic simulations are essential tools in chemistry and materials science, accelerating the discovery of novel catalysts, energy storage materials, and pharmaceuticals. However,…
AI Assistants to Enhance and Exploit the PETSc Knowledge Base
Barry Smith, Junchao Zhang, Hong Zhang +7
Generative AI, especially through large language models (LLMs), is transforming how technical knowledge can be accessed, reused, and extended. PETSc, a widely used numerical librar…
EAIRA: Establishing a Methodology for Evaluating AI Models as Scientific Research Assistants
Franck Cappello, Sandeep Madireddy, Robert Underwood +23
Recent advancements have positioned AI, and particularly Large Language Models (LLMs), as transformative tools for scientific research, capable of addressing complex tasks that req…