Daniel Johnson

1.6k citations
15 papers · 322 indexed · h-index 7

Daniel Johnson

14 papers receiving 301 citations

Peers

Daniel Johnson
Comparison fields: 5 of 32
  • Hardware and Architecture 283
  • Computer Networks and Communications 260
  • Computer Graphics and Computer-Aided Design 15
  • Information Systems 49
  • Computer Vision and Pattern Recognition 27
Replace John H. Kelm with:
John H. Kelm United States
B. Juurlink Netherlands
Amir Kavyan Ziabari United States
Mike Mantor United States
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J.L. Lo United States
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Daniel Johnson relative to John H. Kelm United States John H. Kelm's profile →
Citations per field
00.5×10×
John H. Kelm · 1×
Citations per year

Countries citing papers authored by Daniel Johnson

Since Specialization
Citations

This map shows the geographic impact of Daniel Johnson's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Johnson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Johnson more than expected).

Fields of papers citing papers by Daniel Johnson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Johnson. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Johnson. The network helps show where Daniel Johnson may publish in the future.

Co-authorship network

The 25 scholars most cited alongside Daniel Johnson, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel Johnson Line = papers co-authored together Daniel Johnson links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1 20232
2 20222
3
$B \rightarrow D\bar{D}h$ decays : a new (virtual) laboratory for exotic particle searches at LHCb
20201
4 201567
5 20133
6 20137
7 201115
8 201044
9 20100
10 20104
11 200912
12 2009113
13 20096
14 200842
15
SChISM: Scalable Cache Incoherent Shared Memory
20084

About Daniel Johnson

Daniel Johnson is a scholar working on Hardware and Architecture, Computer Networks and Communications, Statistics, Probability and Uncertainty, Artificial Intelligence and Information Systems, having authored 15 papers that have together received 322 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (10 papers), Advanced Data Storage Technologies (6 papers), Interconnection Networks and Systems (5 papers), Distributed and Parallel Computing Systems (5 papers), Cloud Computing and Resource Management (2 papers), Speech Recognition and Synthesis (2 papers), Particle physics theoretical and experimental studies (1 paper) and Speech and dialogue systems (1 paper). The work is most often cited by research in Hardware and Architecture (283 citations), Computer Networks and Communications (260 citations), Computer Graphics and Computer-Aided Design (15 citations), Information Systems (49 citations) and Computer Vision and Pattern Recognition (27 citations). Daniel Johnson has collaborated with scholars based in United States, United Kingdom and Israel. Frequent co-authors include Sanjay J. Patel, John H. Kelm, Steven S. Lumetta, Aqeel Mahesri, Neal Crago, Matthew I. Frank, Matthew R. Johnson, Mike O’Connor, Mattan Erez and Doug Burger. Their work appears in journals such as IEEE Micro, Journal of Computational Physics, ACM SIGARCH Computer Architecture News, CERN Document Server (European Organization for Nuclear Research) and Illinois Digital Environment for Access to Learning and Scholarship (University of Illinois at Urbana-Champaign).

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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