Greg Hamerly

5.5k citations
35 papers · 3.6k indexed · 1 hit paper · h-index 20

Impact in

Papers in

Greg Hamerly

33 papers receiving 3.4k citations

Hit Papers

Automatically characterizing large scale program behavior 2002 · 1.3k citations
1.3k20022026201020184008001.2k

Peers

Greg Hamerly
Comparison fields: 5 of 135
  • Hardware and Architecture 2.3k
  • Computer Networks and Communications 1.9k
  • Information Systems 653
  • Artificial Intelligence 774
  • Signal Processing 257
Replace Henri E. Bal with:
Henri E. Bal Netherlands
Walid Najjar United States
Eduard Ayguadé Spain
Mateo Valero Spain
W. Richard Stevens United States
Kimberly Keeton United States
Xipeng Shen United States
Feng Chen China
Michael T. Goodrich United States
Howard Jay Siegel United States
Greg Hamerly relative to Henri E. Bal Netherlands Henri E. Bal's profile →
Citations per field
00.5×1.5×2.1×
Henri E. Bal · 1×
Citations per year

Countries citing papers authored by Greg Hamerly

Since Specialization
Citations

This map shows the geographic impact of Greg Hamerly'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 Greg Hamerly with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Greg Hamerly more than expected).

Fields of papers citing papers by Greg Hamerly

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Greg Hamerly. 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 Greg Hamerly. The network helps show where Greg Hamerly may publish in the future.

Co-authors

The 25 scholars most cited alongside Greg Hamerly, 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 Greg Hamerly Line = papers co-authored together Greg Hamerly links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20240
3 20232
4 20238
5 201924
6 20169
7 201417
8 20148
9 2010111
10
Using Machine Learning to Guide Architecture Simulation
200610
11 20063
12 200551
13 200561
14 200497
15 2003145
16
Learning the k in k-means
2003419
17 2003198
18 2002284
19 200237
20 200232

About Greg Hamerly

Greg Hamerly is a scholar working on Hardware and Architecture, Computer Networks and Communications, Ophthalmology, Artificial Intelligence and Information Systems, having authored 35 papers that have together received 3.6k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (17 papers), Software System Performance and Reliability (9 papers), Advanced Clustering Algorithms Research (7 papers), Software Engineering Research (6 papers), Embedded Systems Design Techniques (5 papers), Advanced Data Storage Technologies (4 papers), Face and Expression Recognition (4 papers) and Algorithms and Data Compression (4 papers). The work is most often cited by research in Hardware and Architecture (2.3k citations), Computer Networks and Communications (1.9k citations), Information Systems (653 citations), Artificial Intelligence (774 citations) and Signal Processing (257 citations). Greg Hamerly has collaborated with scholars based in United States. Frequent co-authors include Brad Calder, Erez Perelman, Timothy Sherwood, Charles Elkan, Jeremy Lau, Michael Van Biesbrouck, Suleyman Sair, J. Lau, John J. Sampson and Bryan F. Shaw. Their work appears in journals such as ACM SIGMETRICS Performance Evaluation Review, ACM SIGPLAN Notices, Aquacultural Engineering, BMC Ophthalmology and Science Advances.

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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