Neil R. Euliano

38 papers receiving 1.2k citations

Hit Papers

Neural and adaptive systems: fundamentals through simulat...20002026200820172000200400600

Peers

Neil R. Euliano
Comparison fields: 5 of 152
  • Artificial Intelligence 292
  • Pulmonary and Respiratory Medicine 215
  • Biomedical Engineering 212
  • Electrical and Electronic Engineering 162
  • Pediatrics, Perinatology and Child Health 160
Replace Barrie Hayes‐Gill with:
Barrie Hayes‐Gill United Kingdom
Dingchang Zheng United Kingdom
Sanjay Purushotham United States
Jian Qing Shi China
Fırat Hardalaç Türkiye
Alistair Shilton Australia
Javier Cabrera United States
Si Si China
Yasunobu Nohara Japan
Naimul Khan Canada
Neil R. Euliano relative to Barrie Hayes‐Gill United Kingdom Barrie Hayes‐Gill's profile →
Citations per field
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Barrie Hayes‐Gill · 1×
Citations per year

Countries citing papers authored by Neil R. Euliano

Since Specialization
Citations

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

Fields of papers citing papers by Neil R. Euliano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Neil R. Euliano. 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 Neil R. Euliano. The network helps show where Neil R. Euliano may publish in the future.

Co-authorship network of co-authors of Neil R. Euliano

This figure shows the co-authorship network connecting the top 25 collaborators of Neil R. Euliano. A scholar is included among the top collaborators of Neil R. Euliano based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Neil R. Euliano. Neil R. Euliano is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 1
3 2
4 0
5 2
6 1
7 8
8 4
9 155
10 19
11 68
12 12
13 4
14
On Proper Handling of Multi-collinear Inputs and Errors-in-Variables with Explicit and Implicit Neural Models
1
15 15
16 3
17 19
18
Adaptive and neural inverse control: adaptively controlling a ventilator
1
19
Neural and adaptive systems : fundamentals through simulationsbreakdown →
624
20
Neural and Adaptive Systems: Fundamentals through Simulations with CD-ROM
140

About Neil R. Euliano

Neil R. Euliano is a scholar working on Critical Care and Intensive Care Medicine, Architecture and Medical Laboratory Technology, having authored 40 papers that have together received 1.3k indexed citations. Recurring topics across this work include Respiratory Support and Mechanisms (14 papers), Neural Networks and Applications (7 papers) and Neonatal Respiratory Health Research (6 papers). The work is most often cited by research in Signal Processing (132 citations), Obstetrics and Gynecology (76 citations) and Artificial Intelligence (292 citations). Neil R. Euliano has collaborated with scholars based in United States, Slovakia and Slovenia. Frequent co-authors include José C. Prı́ncipe, William Lefebvre, T. Y. Euliano, Minh Tam Nguyen, Anthony R. Gregg, Susan P. McGorray, Andrea Gabrielli, Michael J. Banner, Rodney K. Edwards and A. Daniel Martin. Their work appears in journals such as Proceedings of the IEEE, CHEST Journal and American Journal of Obstetrics and Gynecology.

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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