Nicholas D. Naclerio
- Biomedical Engineering top 10%
- Mechanical Engineering top 10%
- Control and Systems Engineering top 10%
- Condensed Matter Physics top 10%
- Civil and Structural Engineering top 10%
- Co-authors
- Elliot W. HawkesYasemin Ozkan-AydinDaniel I. GoldmanDavid A. HaggertyEnes AydınBrian P. MannCyrille StéphanGuilhem Michon
- Topics
- Soft Robotics and Applications (13 papers)Modular Robots and Swarm Intelligence (9 papers)Robot Manipulation and Learning (4 papers)
- Partner nations
- United StatesJapanItaly
In The Last Decade
Nicholas D. Naclerio
17 papers receiving 470 citations
Peers
Comparison fields: 5 of 51
- Biomedical Engineering 305
- Mechanical Engineering 278
- Control and Systems Engineering 105
- Condensed Matter Physics 101
- Civil and Structural Engineering 96
Countries citing papers authored by Nicholas D. Naclerio
This map shows the geographic impact of Nicholas D. Naclerio'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 Nicholas D. Naclerio with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Nicholas D. Naclerio more than expected).
Fields of papers citing papers by Nicholas D. Naclerio
This network shows the impact of papers produced by Nicholas D. Naclerio. 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 Nicholas D. Naclerio. The network helps show where Nicholas D. Naclerio may publish in the future.
Co-authorship network of co-authors of Nicholas D. Naclerio
This figure shows the co-authorship network connecting the top 25 collaborators of Nicholas D. Naclerio. A scholar is included among the top collaborators of Nicholas D. Naclerio 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 Nicholas D. Naclerio. Nicholas D. Naclerio is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 5 | |
| 2 | 0 | |
| 3 | 6 | |
| 4 | 1 | |
| 5 | 13 | |
| 6 | 23 | |
| 7 | 120 | |
| 8 | 7 | |
| 9 | 2 | |
| 10 | 71 | |
| 11 | 10 | |
| 12 | 27 | |
| 13 | 33 | |
| 14 | 16 | |
| 15 | 6 | |
| 16 | 13 | |
| 17 | 79 | |
| 18 | 41 |
About Nicholas D. Naclerio
Nicholas D. Naclerio is a scholar working on Condensed Matter Physics, Biomedical Engineering and Mechanical Engineering, having authored 18 papers that have together received 473 indexed citations. Recurring topics across this work include Soft Robotics and Applications (13 papers), Modular Robots and Swarm Intelligence (9 papers) and Robot Manipulation and Learning (4 papers). The work is most often cited by research in Condensed Matter Physics (101 citations), Mechanical Engineering (278 citations) and Biomedical Engineering (305 citations). Nicholas D. Naclerio has collaborated with scholars based in United States, Japan and Italy. Frequent co-authors include Elliot W. Hawkes, Yasemin Ozkan-Aydin, Daniel I. Goldman, David A. Haggerty, Enes Aydın, Brian P. Mann, Cyrille Stéphan, Guilhem Michon, Christian Hubicki and Bruno Siciliano. Their work appears in journals such as Journal of Sound and Vibration, Science Robotics and IEEE Robotics and Automation Letters.
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.