2 citations · 2 across the 5 of their papers we have counts for
5 papers
Data-Driven Spectral Prediction for Accelerating Large-Scale Electronic Structure Calculations
Abhiram Badrinarayanan, Davor Davidovic, Edoardo Di Napoli +4
Simulating large molecular systems comprising thousands of atoms requires highly scalable methodologies. While modern Density Functional Theory (DFT) codes exhibit linear scaling,…
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…
LARA: Validation-Driven Agentic Supercomputer Workflows for Atomistic Modeling
William Dawson, Louis Beal, Yoann Curé +3
Large language models (LLMs) and agentic systems have recently demonstrated potential for automating scientific workflows, including atomistic simulations. However, their deploymen…
Coupling Quantum Mechanical Modeling and Molecular Dynamics on Heterogeneous Supercomputers for Studying Distal Mutation Effects on Drug Binding in HIV-1
William Dawson, Louis Beal, Marco Zaccaria +1
Predicting how protein mutations affect drug binding remains a major challenge, particularly when the mutations are distal from the binding site. In this study, we introduce a coup…
Exploratory Data Science on Supercomputers for Quantum Mechanical Calculations
William Dawson, Louis Beal, Laura E. Ratcliff +3
Literate programming - the bringing together of program code and natural language narratives - has become a ubiquitous approach in the realm of data science. This methodology is ap…