activity
20172024
most citedModular Resource Centric Learning for Workflow Performance Prediction

3 citations · 3 across the 5 of their papers we have counts for

collaborators

6 papers

cs.LG2024

Towards an Integrated Performance Framework for Fire Science and Management Workflows

H. Ahmed, R. Shende, I. Perez +3

Reliable performance metrics are necessary prerequisites to building large-scale end-to-end integrated workflows for collaborative scientific research, particularly within context…

cs.CV2022

Multimodal Wildland Fire Smoke Detection

Siddhant Baldota, Shreyas Anantha Ramaprasad, Jaspreet Kaur Bhamra +9

Research has shown that climate change creates warmer temperatures and drier conditions, leading to longer wildfire seasons and increased wildfire risks in the United States. These…

cs.DC2019

Workflow-Driven Distributed Machine Learning in CHASE-CI: A Cognitive Hardware and Software Ecosystem Community Infrastructure

Ilkay Altintas, Kyle Marcus, Isaac Nealey +7

The advances in data, computing and networking over the last two decades led to a shift in many application domains that includes machine learning on big data as a part of the scie…

cs.CY2019

Towards A Methodology and Framework for Workflow-Driven Team Science

Ilkay Altintas, Shweta Purawat, Daniel Crawl +2

Scientific workflows are powerful tools for management of scalable experiments, often composed of complex tasks running on distributed resources. Existing cyberinfrastructure provi…

cs.CL2018

Enabling FAIR Research in Earth Science through Research Objects

Andres Garcia-Silva, Jose Manuel Gomez-Perez, Raul Palma +24

Data-intensive science communities are progressively adopting FAIR practices that enhance the visibility of scientific breakthroughs and enable reuse. At the core of this movement,…

cs.DC2017★ 3 cited

Modular Resource Centric Learning for Workflow Performance Prediction

Alok Singh, Mai Nguyen, Shweta Purawat +2

Workflows provide an expressive programming model for fine-grained control of large-scale applications in distributed computing environments. Accurate estimates of complex workflow…