activity
20182026
most cited14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon

214 citations · 482 across the 18 of their papers we have counts for

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5 papers · 1 filter

cs.DC20252 cited

Experiences with Model Context Protocol Servers for Science and High Performance Computing

Haochen Pan, Ryan Chard, Reid Mello +12

Large language model (LLM)-powered agents are increasingly used to plan and execute scientific workflows, yet most research cyberinfrastructure (CI) exposes heterogeneous APIs and…

cs.DC202233 cited

funcX: Federated Function as a Service for Science

Zhuozhao Li, Ryan Chard, Yadu Babuji +9

funcX is a distributed function as a service (FaaS) platform that enables flexible, scalable, and high performance remote function execution. Unlike centralized FaaS systems, funcX…

cs.DC2020

IMPECCABLE: Integrated Modeling PipelinE for COVID Cure by Assessing Better LEads

Aymen Al Saadi, Dario Alfe, Yadu Babuji +33

The drug discovery process currently employed in the pharmaceutical industry typically requires about 10 years and $2-3 billion to deliver one new drug. This is both too expensive…

cs.DC2020193 cited

funcX: A Federated Function Serving Fabric for Science

Ryan Chard, Yadu Babuji, Zhuozhao Li +5

Exploding data volumes and velocities, new computational methods and platforms, and ubiquitous connectivity demand new approaches to computation in the sciences. These new approach…

cs.DC2019

Serverless Supercomputing: High Performance Function as a Service for Science

Ryan Chard, Tyler J. Skluzacek, Zhuozhao Li +6

Growing data volumes and velocities are driving exciting new methods across the sciences in which data analytics and machine learning are increasingly intertwined with research. Th…