activity
20192026
most cited2022 Review of Data-Driven Plasma Science

85 citations · 90 across the 5 of their papers we have counts for

collaborators

6 papers

cs.DC2026

Unstructured Hydrodynamics on Spatial Dataflow Architectures: A Joint Code and Data Decomposition Approach

Piotr Luczynski, Tal Ben-Nun, Leighton Wilson +1

Spatial Dataflow Architectures are an emerging hardware pattern in high-performance computing, whose mesh-connected fixed-memory processing elements are tailored for structured gri…

physics.chem-ph2025★ 1 cited

The Open Polymers 2026 (OPoly26) Dataset and Evaluations

Daniel S. Levine, Nicholas Liesen, Lauren Chua +12

Polymers-macromolecular systems composed of repeating chemical units-constitute the molecular foundation of living organisms, while their synthetic counterparts drive transformativ…

cs.LG2025

BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models

Evan R. Antoniuk, Shehtab Zaman, Tal Ben-Nun +10

Data-driven molecular discovery leverages artificial intelligence/machine learning (AI/ML) and generative modeling to filter and design novel molecules. Discovering novel molecules…

physics.plasm-ph2022★ 85 cited

2022 Review of Data-Driven Plasma Science

Rushil Anirudh, Rick Archibald, M. Salman Asif +60

Data science and technology offer transformative tools and methods to science. This review article highlights latest development and progress in the interdisciplinary field of data…

cs.DC2021

Is Disaggregation possible for HPC Cognitive Simulation?

Michael R Wyatt, Valen Yamamoto, Zoe Tosi +2

Cognitive simulation (CogSim) is an important and emerging workflow for HPC scientific exploration and scientific machine learning (SciML). One challenging workload for CogSim is t…

cs.DC2019★ 4 cited

Enabling Machine Learning-Ready HPC Ensembles with Merlin

J. Luc Peterson, Ben Bay, Joe Koning +17

With the growing complexity of computational and experimental facilities, many scientific researchers are turning to machine learning (ML) techniques to analyze large scale ensembl…