L.M. Hively

1.8k citations
59 papers · 1.3k indexed · h-index 17

Impact in

Papers in

L.M. Hively

55 papers receiving 1.2k citations

Peers

L.M. Hively
Comparison fields: 5 of 111
  • Nuclear and High Energy Physics 336
  • Statistical and Nonlinear Physics 286
  • Cognitive Neuroscience 401
  • Signal Processing 181
  • Economics and Econometrics 181
Replace Dipak Ghosh with:
Dipak Ghosh India
Bernd Schürmann Germany
S.J. Orfanidis United States
D. Bollé Belgium
M. Pellicoro Italy
V. Protopopescu United States
Toshimitsu Musha Japan
А. А. Короновский Russia
Willard L. Miranker United States
Tanya Schmah Canada
L.M. Hively relative to Dipak Ghosh India Dipak Ghosh's profile →
Citations per field
00.5×1.7×
Dipak Ghosh · 1×
Citations per year

Countries citing papers authored by L.M. Hively

Since Specialization
Citations

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

Fields of papers citing papers by L.M. Hively

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by L.M. Hively. 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 L.M. Hively. The network helps show where L.M. Hively may publish in the future.

Co-authors

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

All Works

20 of 20 papers shown
#Work
1
Epileptic seizure prediction by non-linear methods
20230
2
Method and system for reducing errors in vehicle weighing systems
20230
3
Integrated method for chaotic time series analysis
20230
4 201911
5 20188
6 20172
7 2014138
8 20137
9 201217
10
A Vision for Scalable Trustworthy Computing
20102
11 20091
12 2004447
13 200339
14 200132
15 19907
16 19887
17 19862
18 198423
19 19843
20 198316

About L.M. Hively

L.M. Hively is a scholar working on Nuclear and High Energy Physics, Statistical and Nonlinear Physics, Signal Processing, Cognitive Neuroscience and Computer Networks and Communications, having authored 59 papers that have together received 1.3k indexed citations. Recurring topics across this work include Magnetic confinement fusion research (17 papers), Fusion materials and technologies (11 papers), EEG and Brain-Computer Interfaces (10 papers), Neural dynamics and brain function (9 papers), Chaos control and synchronization (8 papers), Fractal and DNA sequence analysis (6 papers), Nuclear reactor physics and engineering (5 papers) and Advanced Malware Detection Techniques (4 papers). The work is most often cited by research in Nuclear and High Energy Physics (336 citations), Statistical and Nonlinear Physics (286 citations), Cognitive Neuroscience (401 citations), Signal Processing (181 citations) and Economics and Econometrics (181 citations). L.M. Hively has collaborated with scholars based in United States, Denmark and Italy. Frequent co-authors include V. Protopopescu, Jianbo Gao, Yinping Cao, Wen‐wen Tung, George H. Miley, Paul C. Gailey, W. A. Houlberg, S.E. Attenberger, Nancy B. Munro and J. A. Rome. Their work appears in journals such as Nuclear Fusion, Journal of Nuclear Materials, IEEE Security & Privacy, Chaos An Interdisciplinary Journal of Nonlinear Science and IEEE Transactions on Magnetics.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026