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researcher

K. Hazelwood

4 papers hereh-index 7958 citations19 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author2

Across the 2 of 4 papers where every author was matched, so the position is known.

fields
  • physics.acc-ph3
  • cs.LG1
same name
  • K. Hazelwood — 13 papers, h 32
  • K. Hazelwood — 2 papers, h 3
  • K. Hazelwood — 1 paper, h 3

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20212023
most citedApplications and Techniques for Fast Machine Learning in Science

77 citations · 79 across the 4 of their papers we have counts for

collaborators

4 papers

physics.acc-ph2023

The Ionization Profile Monitors in the Recycler Ring

B. Babacan, R. Ainsworth, K. J. Hazelwood +2

The ionization profile monitors (IPMs) are used to measure the beam size in synchrotrons. Both the Fermilab Recycler and Main Injector (MI) machines have IPMs. However, they were n…

physics.acc-ph2022★ 2 cited

Synchronous High-frequency Distributed Readout For Edge Processing At The Fermilab Main Injector And Recycler

J. R. Berlioz, M. R. Austin, J. M. Arnold +17

The Main Injector (MI) was commissioned using data acquisition systems developed for the Fermilab Main Ring in the 1980s. New VME-based instrumentation was commissioned in 2006 for…

cs.LG2021★ 77 cited

Applications and Techniques for Fast Machine Learning in Science

Allison McCarn Deiana, Nhan Tran, Joshua Agar +84

In this community review report, we discuss applications and techniques for fast machine learning (ML) in science -- the concept of integrating power ML methods into the real-time…

physics.acc-ph2021

Accelerator Real-time Edge AI for Distributed Systems (READS) Proposal

K. Seiya, K. J. Hazelwood, M. A. Ibrahim +7

Our objective will be to integrate ML into Fermilab accelerator operations and furthermore provide an accessible framework which can also be used by a broad range of other accelera…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.