Matt Baughman - Minerva Schools at KGI, San Francisco, CA, USA

基本信息

Career Trajectory

Bio

Matt Baughman (mbaughman@uchicago.edu) is a 5th year Ph.D. student at the University of Chicago in Chicago, Illinois, USA where he earned his master degree in computer science. His research focuses on cost-aware computing, federated learning, and distributed computing. Prior, Matt attended Minerva University in San Francisco, California, USA where he earned a dual B.Sc. and B.A. in computer science and philosophy.

Research Interests

Papers共 28 篇Author StatisticsCo-AuthorSimilar Experts

By YearBy Citation主题筛选期刊级别筛选合作者筛选合作机构筛选

RuralAI in Tomato Farming: Integrated Sensor System, Distributed Computing, and Hierarchical Federated Learning for Crop Health Monitoring

Harish Devaraj,Shaleeza Sohail,Melanie Ooi,Boyang Li,Nathaniel Hudson,Matt Baughman,Kyle Chard,Ryan Chard,Enrico Casella,Ian Foster,Omer Rana

IEEE sensors lettersno. 5 (2024): 1-4

Cited0Views0EIWOSBibtex

Enabling Remote Management of FaaS Endpoints with Globus Compute Multi-User Endpoints

Rachana Ananthakrishnan, Yadu Babuji,Matt Baughman,Josh Bryan,Kyle Chard,Ryan Chard,Ben Clifford,Ian Foster,Daniel S. Katz, Kevin Hunter Kesling, Chris Janidlo, Reid Mello, Lei Wang

PRACTICE AND EXPERIENCE IN ADVANCED RESEARCH COMPUTING 2024, PEARC 2024 (2024)

Cited0Views0EIBibtex

QoS-aware Edge AI Placement and Scheduling with Multiple Implementations in FaaS-based Edge Computing

Nathaniel Hudson,Hana Khamfroush,Matt Baughman,Daniel E. Lucani,Kyle Chard,Ian Foster

Future generation computer systems (2024): 250-263

Cited0Views0EIBibtex

Flight: A FaaS-Based Framework for Complex and Hierarchical Federated Learning

Nathaniel Hudson,Valerie Hayot-Sasson, Yadu Babuji,Matt Baughman, J. Gregory Pauloski,Ryan Chard,Ian Foster,Kyle Chard

arxiv（2024）

Cited0Views0Bibtex

Unveiling Temporal Performance Deviation: Leveraging Clustering in Microservices Performance Analysis

Andre Bauer, Timo Dittus,Martin Straesser,Alok Kamatar,Matt Baughman,Lukas Beierlieb,Marius Hadry, Daniel Grillmeyer, Yannik Lubas,Samuel Kounev,Ian Foster,Kyle Chard

COMPANION OF THE 15TH ACM/SPEC INTERNATIONAL CONFERENCE ON PERFORMANCE ENGINEERING, ICPE COMPANION 2...（2024）

Cited0Views0EIBibtex

An Empirical Investigation of Container Building Strategies and Warm Times to Reduce Cold Starts in Scientific Computing Serverless Functions

André Bauer, Maxime Gonthier, Haochen Pan,Ryan Chard, Daniel Grzenda,Martin Straesser, J. Gregory Pauloski, Alok Kamatar,Matt Baughman,Nathaniel Hudson,Ian Foster,Kyle Chard

2024 IEEE 20th International Conference on e-Science (e-Science)pp.1-10, (2024)

Cited0Views0EIWOSBibtex

Tournament-Based Pretraining to Accelerate Federated Learning

Matt Baughman,Nathaniel Hudson,Ryan Chard,André Bauer ,Ian T. Foster,Kyle Chard

SC-W '23: Proceedings of the SC '23 Workshops of The International Conference on High Performance Computing, Network, Storage, and Analysispp.109-115, (2023)

Cited0Views0EIBibtex

Balancing Federated Learning Trade-Offs for Heterogeneous Environments

Matt Baughman,Nathaniel Hudson,Ian T. Foster,Kyle Chard

PerCom Workshopspp.404-407, (2023)

Cited0Views0EIWOSBibtex

Trillion Parameter AI Serving Infrastructure for Scientific Discovery: A Survey and Vision

Nathaniel Hudson,J. Gregory Pauloski,Matt Baughman,Alok Kamatar,Mansi Sakarvadia,Logan Ward,Ryan Chard,Andre Bauer,Maksim Levental, Wenyi Wang, Will Engler, Owen Price Skelly,Ben Blaiszik,Rick Stevens,Kyle Chard,Ian Foster

PROCEEDINGS OF THE IEEE/ACM 10TH INTERNATIONAL CONFERENCE ON BIG DATA COMPUTING, APPLICATIONS AND TECHNOLOGIES, BDCAT 2023 (2023)

Cited0Views0EIBibtex

Accelerating Communications in Federated Applications with Transparent Object Proxies

J. Gregory Pauloski,Valerie Hayot-Sasson,Logan Ward,Nathaniel Hudson,Charlie Sabino,Matt Baughman,Kyle Chard,Ian Foster

International Conference on Software Composition (2023)

Cited0Views0EIWOSBibtex

Author Statistics

Co-Author

Co-Institution

D-Core

合作者
学生
导师

No result temporarily, you can search similar Scholar with the same research interest

Data Disclaimer

The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn