Nathaniel (Nathaniel Hudson) has been selected to serve on 2 TPCs for PERCOM's WiP 2023 session and DCOSS-IoT 2023.

Matt Baughman and Nathaniel Hudson had their paper "Balancing Federated Learning Trade-Offs for Heterogeneous Environments" accepted to the Work in Progress session at IEEEPerCom. Congrats! 🎉

Nathaniel Hudson will be travelling in style (with a travel grant!) to present his work on resource and performance tradeoffs in federated learning at the 2023 meeting of Pervasive Computing #federatedlearning #ml #edgecomputing

@AndrBauer1 had his paper "Efficient Data Processing: Assessing the Performance of Different Programming Languages" and another paper co-authored with Nathaniel Hudson "Searching for the Ground Truth: Assessing the Similarity of Benchmarking Runs" accepted to the ICPE 2025. Congrats!

A Work-in-Progress paper on balancing federated learning trade-offs, authored by Ph.D. candidate Matt Baughman, postdoctoral scholar Nathaniel (Nathaniel Hudson), et al., was awarded the Best WiP paper award at the 2023 IEEEPerCom conference!

What an enriching summer research #internship at #globus Globus Labs Globus! Grateful for the opportunity to learn, grow and contribute. Thanks for cherished memories with my new friends. Logan Ward Nathaniel Hudson A special shoutout to my mentor, Dr. Kyle Chard Kyle Chard

Congrats to Globus Labs postdoc Nathaniel Hudson for his seat on the on the technical program committee for the IEEE DCOS S-IoT 2024 in Abu Dhabi this fall! #IoT #distributedcomputing

Nathaniel's (Nathaniel Hudson) WF-IoT paper, entitled “Adversarial Predictions of Data Distributions Across Federated Internet-of-Things Devices”, in collaboration with members from SAGE got accepted in the main conference track at IEEE WF-IoT (arxiv.org/abs/2308.14658)

Our first RuralAI (ruralai.org) workshop led by Melanie Oii The University of Waikato 🎓 & Shaleeza Sohail University of Newcastle international University networks are key to address global challenges. Kyle Chard Nathaniel Hudson Nitin Auluck/नितिन औलक Ashish Kaushal. Join the conversation: sites.google.com/view/rural-ai/…

and our illustrious post-doc scholar Nathaniel Hudson (Nathaniel Hudson) will explore "Federated Learning on Globus Compute using FLoX." 🖥️🌐

It was great to see everyone from the Parsl (@[email protected]) community at ParslFest! Check out the talks from Logan Ward, Yadu Nand Babuji, Nathaniel Hudson, Val Hayot, Matt, Greg and many others on the ParslFest website: parsl-project.org/parslfest/pars…

Attention Lens (arxiv.org/abs/2310.16270) was accepted to the NEURIPS Attributing Model Behavior at Scale Workshop (attrib-workshop.cc) NeurIPS Conference. Congratulations Mansi Sakarvadia, Arham Khan, Aswathy Ajith, Daniel Grzenda, Nathaniel Hudson, @AndrBauer1, Kyle Chard, Ian Foster

Check out our new paper surveying modern approaches to serving Trillion Parameter models, a part of our effort to create robust AI infrastructure for AI in Science: arxiv.org/abs/2402.03480. Congrats Nathaniel Hudson, Greg Pauloski, Matthew Baughman, Alok Kamatar, Mansi Sakarvadia, and others!

My recent publication on QoS-aware placement and scheduling of Edge AI featured in Future Generation Computer Systems (@comp_science) is now publicly available. From now until May 26 2024, the link below will give you access to the paper for free. 😄 authors.elsevier.com/a/1itvR,3q5xo1…

Our postdoc, Nathaniel Hudson (Nathaniel Hudson), has been selected to participate in the 2024 CPS Rising Stars workshop at the University of Virginia. The acceptance rate was ~16%. Amazing job, Nathaniel! risingstars.linklab.virginia.edu/2024/

Hallucinations in GPT models are a huge problem. A lot of this relates to the trust that we extend to these models. That said, this is a relevant read and an important story to follow. politico.eu/article/chatgp…

This is a thread on research our group at The University of Chicago recently made public on how to address the phenomenon of "memorized" data in large language models (#LLMs). The preprint is public and a blog is available for a lighter read (see thread). Check it out! 📰#MachineLearning #AI

Excited to share our latest work: "SoK: On Finding Common Ground in Loss Landscapes Using Deep Model Merging Techniques"! 🧠 arxiv.org/abs/2410.12927 By Arham Khan, Todd Nief, Nathaniel Hudson, Mansi Sakarvadia, Daniel Grzenda, Aswathy Ajith, Jordan Pettyjohn, Kyle Chard, and Ian Foster.

I am super proud of Jordan Pettyjohn, an undergraduate student I had the privilege of working with this past summer, for winning the Student Research Competition at the SC25 conference! 🏆 His work studied ablation strategies for toxicity in #LLMs.