Nathaniel Hudson

46 papers A 2B 7C 1Misc 2Journal 25Unranked 9

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Flight: A FaaS-based framework for complex and Hierarchical Federated Learning. Future Gener. Comput. Syst. Nathaniel Hudson, Valérie Hayot-Sasson, Yadu Nand Babuji, Matt Baughman, J. Gregory Pauloski, Ryan Chard, Ian T. Foster, Kyle Chard
2025	J	`jnl`	AERO: An autonomous platform for continuous research. CoRR Valérie Hayot-Sasson, Abby Stevens, Nicholson T. Collier, Sudershan Sridhar, Kyle Conroy, J. Gregory Pauloski, Yadu N. Babuji, Maxime Gonthier, Nathaniel Hudson, Dante D. Sánchez-Gallegos, Ian T. Foster, Jonathan Ozik, Kyle Chard
2025	A	`conf`	Addressing Reproducibility Challenges in HPC with Continuous Integration. SC Valérie Hayot-Sasson, Nathaniel Hudson, André Bauer, Maxime Gonthier, Ian T. Foster, Kyle Chard
2025	J	`jnl`	Addressing Reproducibility Challenges in HPC with Continuous Integration. CoRR Valérie Hayot-Sasson, Nathaniel Hudson, André Bauer, Maxime Gonthier, Ian T. Foster, Kyle Chard
2025	J	`jnl`	MOFA: Discovering Materials for Carbon Capture with a GenAI- and Simulation-Based Workflow. CoRR Xiaoli Yan, Nathaniel Hudson, Hyun Park, Daniel Grzenda, J. Gregory Pauloski, Marcus Schwarting, Haochen Pan, Hassan Harb, Sam Foreman, Chris Knight, Tom Gibbs, Kyle Chard, Santanu Chaudhuri, Emad Tajkhorshid, Ian T. Foster, Mohamad Moosavi, Logan T. Ward, Eliu A. Huerta
2025	—	`conf`	Steering an Active Learning Workflow Towards Novel Materials Discovery via Queue Prioritization. eScience Marcus Schwarting, Logan T. Ward, Nathaniel Hudson, Xiaoli Yan, Ben Blaiszik, Santanu Chaudhuri, Eliu A. Huerta, Ian T. Foster
2025	J	`jnl`	Steering an Active Learning Workflow Towards Novel Materials Discovery via Queue Prioritization. CoRR Marcus Schwarting, Logan T. Ward, Nathaniel Hudson, Xiaoli Yan, Ben Blaiszik, Santanu Chaudhuri, Eliu A. Huerta, Ian T. Foster
2025	J	`jnl`	Topology-Aware Knowledge Propagation in Decentralized Learning. CoRR Mansi Sakarvadia, Nathaniel Hudson, Tian Li, Ian T. Foster, Kyle Chard
2024	B	`conf`	An Empirical Investigation of Container Building Strategies and Warm Times to Reduce Cold Starts in Scientific Computing Serverless Functions. e-Science André Bauer, Maxime Gonthier, Haochen Pan, Ryan Chard, Daniel Grzenda, Martin Straesser, J. Gregory Pauloski, Alok Kamatar, Matt Baughman, Nathaniel Hudson, Ian T. Foster, Kyle Chard
2024	J	`jnl`	Causal Discovery over High-Dimensional Structured Hypothesis Spaces with Causal Graph Partitioning. CoRR Ashka Shah, Adela DePavia, Nathaniel Hudson, Ian T. Foster, Rick Stevens
2024	J	`jnl`	Deadline-Aware Task Offloading for Vehicular Edge Computing Networks Using Traffic Light Data. ACM Trans. Embed. Comput. Syst. Pratham Oza, Nathaniel Hudson, Thidapat Chantem, Hana Khamfroush
2024	J	`jnl`	Flight: A FaaS-Based Framework for Complex and Hierarchical Federated Learning. CoRR Nathaniel Hudson, Valérie Hayot-Sasson, Yadu N. Babuji, Matt Baughman, J. Gregory Pauloski, Ryan Chard, Ian T. Foster, Kyle Chard
2024	J	`jnl`	Mitigating Memorization In Language Models. CoRR Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Nathaniel Hudson, Caleb Geniesse, Kyle Chard, Yaoqing Yang, Ian T. Foster, Michael W. Mahoney
2024	J	`jnl`	QoS-aware edge AI placement and scheduling with multiple implementations in FaaS-based edge computing. Future Gener. Comput. Syst. Nathaniel Hudson, Hana Khamfroush, Matt Baughman, Daniel E. Lucani, Kyle Chard, Ian T. Foster
2024	J	`jnl`	SoK: On Finding Common Ground in Loss Landscapes Using Deep Model Merging Techniques. CoRR Arham Khan, Todd Nief, Nathaniel Hudson, Mansi Sakarvadia, Daniel Grzenda, Aswathy Ajith, Jordan Pettyjohn, Kyle Chard, Ian T. Foster
2024	B	`conf`	TaPS: A Performance Evaluation Suite for Task-based Execution Frameworks. e-Science J. Gregory Pauloski, Valérie Hayot-Sasson, Maxime Gonthier, Nathaniel Hudson, Haochen Pan, Sicheng Zhou, Ian T. Foster, Kyle Chard
2024	J	`jnl`	TaPS: A Performance Evaluation Suite for Task-based Execution Frameworks. CoRR J. Gregory Pauloski, Valérie Hayot-Sasson, Maxime Gonthier, Nathaniel Hudson, Haochen Pan, Sicheng Zhou, Ian T. Foster, Kyle Chard
2024	J	`jnl`	Thinking in Categories: A Survey on Assessing the Quality for Time Series Synthesis. ACM J. Data Inf. Qual. Michael Stenger, André Bauer, Thomas Prantl, Robert Leppich, Nathaniel Hudson, Kyle Chard, Ian T. Foster, Samuel Kounev
2024	J	`jnl`	Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision. CoRR Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman, Alok Kamatar, Mansi Sakarvadia, Logan T. Ward, Ryan Chard, André Bauer, Maksim Levental, Wenyi Wang, Will Engler, Owen Price Skelly, Ben Blaiszik, Rick Stevens, Kyle Chard, Ian T. Foster
2023	A	`conf`	Accelerating Communications in Federated Applications with Transparent Object Proxies. SC J. Gregory Pauloski, Valérie Hayot-Sasson, Logan T. Ward, Nathaniel Hudson, Charlie Sabino, Matt Baughman, Kyle Chard, Ian T. Foster
2023	J	`jnl`	Accelerating Communications in Federated Applications with Transparent Object Proxies. CoRR J. Gregory Pauloski, Valérie Hayot-Sasson, Logan T. Ward, Nathaniel Hudson, Charlie Sabino, Matt Baughman, Kyle Chard, Ian T. Foster
2023	—	`conf`	Adversarial Predictions of Data Distributions Across Federated Internet-of-Things Devices. WF-IoT Samir Rajani, Dario Dematties, Nathaniel Hudson, Kyle Chard, Nicola J. Ferrier, Rajesh Sankaran, Peter H. Beckman
2023	J	`jnl`	Adversarial Predictions of Data Distributions Across Federated Internet-of-Things Devices. CoRR Samir Rajani, Dario Dematties, Nathaniel Hudson, Kyle Chard, Nicola J. Ferrier, Rajesh Sankaran, Peter H. Beckman
2023	J	`jnl`	Attention Lens: A Tool for Mechanistically Interpreting the Attention Head Information Retrieval Mechanism. CoRR Mansi Sakarvadia, Arham Khan, Aswathy Ajith, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian T. Foster
2023	—	`conf`	Balancing Federated Learning Trade-Offs for Heterogeneous Environments. PerCom Workshops Matt Baughman, Nathaniel Hudson, Ian T. Foster, Kyle Chard
2023	J	`jnl`	Hierarchical and Decentralised Federated Learning. CoRR Omer F. Rana, Theodoros Spyridopoulos, Nathaniel Hudson, Matt Baughman, Kyle Chard, Ian T. Foster, Aftab Khan
2023	J	`jnl`	Measurement and Applications: Exploring the Challenges and Opportunities of Hierarchical Federated Learning in Sensor Applications. IEEE Instrum. Meas. Mag. Melanie Po-Leen Ooi, Shaleeza Sohail, Victoria Guiying Huang, Nathaniel Hudson, Matt Baughman, Omer F. Rana, Annika Hinze, Kyle Chard, Ryan Chard, Ian T. Foster, Theodoros Spyridopoulos, Harshaan Nagra
2023	—	`conf`	Memory Injections: Correcting Multi-Hop Reasoning Failures During Inference in Transformer-Based Language Models. BlackboxNLP@EMNLP Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian T. Foster
2023	J	`jnl`	Memory Injections: Correcting Multi-Hop Reasoning Failures during Inference in Transformer-Based Language Models. CoRR Mansi Sakarvadia, Aswathy Ajith, Arham Khan, Daniel Grzenda, Nathaniel Hudson, André Bauer, Kyle Chard, Ian T. Foster
2023	—	`conf`	Searching for the Ground Truth: Assessing the Similarity of Benchmarking Runs. ICPE (Companion) André Bauer, Martin Straesser, Mark Leznik, Lukas Beierlieb, Marius Hadry, Nathaniel Hudson, Kyle Chard, Samuel Kounev, Ian T. Foster
2023	—	`conf`	Tournament-Based Pretraining to Accelerate Federated Learning. SC Workshops Matt Baughman, Nathaniel Hudson, Ryan Chard, André Bauer, Ian T. Foster, Kyle Chard
2023	C	`conf`	Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision. BDCAT Nathaniel Hudson, J. Gregory Pauloski, Matt Baughman, Alok Kamatar, Mansi Sakarvadia, Logan T. Ward, Ryan Chard, André Bauer, Maksim Levental, Wenyi Wang, Will Engler, Owen Price Skelly, Ben Blaiszik, Rick Stevens, Kyle Chard, Ian T. Foster
2022	—	`conf`	Communication-Loss Trade-Off in Federated Learning: A Distributed Client Selection Algorithm. CCNC Minoo Hosseinzadeh, Nathaniel Hudson, Sam Heshmati, Hana Khamfroush
2022	B	`conf`	FLoX: Federated Learning with FaaS at the Edge. e-Science Nikita Kotsehub, Matt Baughman, Ryan Chard, Nathaniel Hudson, Panos Patros, Omer F. Rana, Ian T. Foster, Kyle Chard
2022	B	`conf`	Smart Edge-Enabled Traffic Light Control: Improving Reward-Communication Trade-offs with Federated Reinforcement Learning. SMARTCOMP Nathaniel Hudson, Pratham Oza, Hana Khamfroush, Thidapat Chantem
2021	B	`conf`	A Framework for Edge Intelligent Smart Distribution Grids via Federated Learning. ICCCN Nathaniel Hudson, Md. Jakir Hossain, Minoo Hosseinzadeh, Hana Khamfroush, Mahshid Rahnamay-Naeini, Nasir Ghani
2021	J	`jnl`	Behavioral Information Diffusion for Opinion Maximization in Online Social Networks. IEEE Trans. Netw. Sci. Eng. Nathaniel Hudson, Hana Khamfroush
2021	—	`conf`	Joint Compression and Offloading Decisions for Deep Learning Services in 3-Tier Edge Systems. DySPAN Minoo Hosseinzadeh, Nathaniel Hudson, Xiaobo Zhao, Hana Khamfroush, Daniel E. Lucani
2021	B	`conf`	QoS-Aware Placement of Deep Learning Services on the Edge with Multiple Service Implementations. ICCCN Nathaniel Hudson, Hana Khamfroush, Daniel E. Lucani
2021	J	`jnl`	QoS-Aware Placement of Deep Learning Services on the Edge with Multiple Service Implementations. CoRR Nathaniel Hudson, Hana Khamfroush, Daniel E. Lucani
2020	Misc	`conf`	A Proximity-Based Generative Model for Online Social Network Topologies. ICNC Emory Hufbauer, Nathaniel Hudson, Hana Khamfroush
2020	—	`conf`	Improving the Accuracy-Latency Trade-off of Edge-Cloud Computation Offloading for Deep Learning Services. GLOBECOM (Workshops) Xiaobo Zhao, Minoo Hosseinzadeh, Nathaniel Hudson, Hana Khamfroush, Daniel E. Lucani
2020	B	`conf`	Smart Advertisement for Maximal Clicks in Online Social Networks Without User Data. SMARTCOMP Nathaniel Hudson, Hana Khamfroush, Brent Harrison, Adam Craig
2019	J	`jnl`	Click Maximization in Online Social Networks Using Optimal Choice of Targeted Interests. CoRR Nathaniel Hudson, Hana Khamfroush, Brent Harrison, Adam Craig
2019	J	`jnl`	Influence spread in two-layer interdependent networks: designed single-layer or random two-layer initial spreaders? Appl. Netw. Sci. Hana Khamfroush, Nathaniel Hudson, Samuel Lofumbwa Iloo, Mahshid Rahnamay-Naeini
2019	Misc	`conf`	On the Effectiveness of Standard Centrality Metrics for Interdependent Networks. ICNC Nathaniel Hudson, Matthew Turner, Asare Nkansah, Hana Khamfroush