Logan T. Ward

Orcid: 0000-0002-1323-5939

According to our database1, Logan T. Ward authored at least 37 papers between 2017 and 2024.

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Bibliography

2024
<i>E</i><sub>min</sub>: A First-Principles Thermochemical Descriptor for Predicting Molecular Synthesizability.
J. Chem. Inf. Model., February, 2024

Foundry-ML - Software and Services to Simplify Access to Machine Learning Datasets in Materials Science.
J. Open Source Softw., January, 2024





Workflows Community Summit 2024: Future Trends and Challenges in Scientific Workflows.
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CoRR, 2024

Employing Artificial Intelligence to Steer Exascale Workflows with Colmena.
CoRR, 2024

Object Proxy Patterns for Accelerating Distributed Applications.
CoRR, 2024


Accelerating Function-Centric Applications by Discovering, Distributing, and Retaining Reusable Context in Workflow Systems.
Proceedings of the 33rd International Symposium on High-Performance Parallel and Distributed Computing, 2024

2023
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics.
Int. J. High Perform. Comput. Appl., November, 2023

Accelerating Electronic Stopping Power Predictions by 10 Million Times with a Combination of Time-Dependent Density Functional Theory and Machine Learning.
CoRR, 2023

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies.
CoRR, 2023

14 Examples of How LLMs Can Transform Materials Science and Chemistry: A Reflection on a Large Language Model Hackathon.
CoRR, 2023

Accelerating Communications in Federated Applications with Transparent Object Proxies.
Proceedings of the International Conference for High Performance Computing, 2023

Fine-grained accelerator partitioning for Machine Learning and Scientific Computing in Function as a Service Platform.
Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, 2023

Cloud Services Enable Efficient AI-Guided Simulation Workflows across Heterogeneous Resources.
Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2023

Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision.
Proceedings of the IEEE/ACM 10th International Conference on Big Data Computing, 2023

2022
RADICAL-Pilot and Parsl: Executing Heterogeneous Workflows on HPC Platforms.
Proceedings of the IEEE/ACM Workshop on Workflows in Support of Large-Scale Science, 2022

2021
DLHub: Simplifying publication, discovery, and use of machine learning models in science.
J. Parallel Distributed Comput., 2021

Co-design Center for Exascale Machine Learning Technologies (ExaLearn).
Int. J. High Perform. Comput. Appl., 2021

Evening the Score: Targeting SARS-CoV-2 Protease Inhibition in Graph Generative Models for Therapeutic Candidates.
CoRR, 2021

Benchmarking Deep Graph Generative Models for Optimizing New Drug Molecules for COVID-19.
CoRR, 2021

AI- and HPC-enabled Lead Generation for SARS-CoV-2: Models and Processes to Extract Druglike Molecules Contained in Natural Language Text.
CoRR, 2021

Not All Tasks Are Created Equal: Adaptive Resource Allocation for Heterogeneous Tasks in Dynamic Workflows.
Proceedings of the 2021 IEEE Workshop on Workflows in Support of Large-Scale Science (WORKS), 2021

Colmena: Scalable Machine-Learning-Based Steering of Ensemble Simulations for High Performance Computing.
Proceedings of the IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2021

Proxima: accelerating the integration of machine learning in atomistic simulations.
Proceedings of the ICS '21: 2021 International Conference on Supercomputing, 2021

2020
HydroNet: Benchmark Tasks for Preserving Intermolecular Interactions and Structural Motifs in Predictive and Generative Models for Molecular Data.
CoRR, 2020

2019
Publishing and Serving Machine Learning Models with DLHub.
Proceedings of the Practice and Experience in Advanced Research Computing on Rise of the Machines (learning), 2019

Serverless Workflows for Indexing Large Scientific Data.
Proceedings of the 5th International Workshop on Serverless Computing, 2019

IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery.
Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2019

DLHub: Model and Data Serving for Science.
Proceedings of the 2019 IEEE International Parallel and Distributed Processing Symposium, 2019

Creating Training Data for Scientific Named Entity Recognition with Minimal Human Effort.
Proceedings of the Computational Science - ICCS 2019, 2019

Active Learning Yields Better Training Data for Scientific Named Entity Recognition.
Proceedings of the 15th International Conference on eScience, 2019

2018
Profiling and Predicting Application Performance on the Cloud.
Proceedings of the 11th IEEE/ACM International Conference on Utility and Cloud Computing, 2018

2017
Towards a Hybrid Human-Computer Scientific Information Extraction Pipeline.
Proceedings of the 13th IEEE International Conference on e-Science, 2017


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