Amanda Parker

2.6k total citations
85 papers, 2.1k citations indexed

About

Amanda Parker is a scholar working on Cognitive Neuroscience, Materials Chemistry and Artificial Intelligence. According to data from OpenAlex, Amanda Parker has authored 85 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Cognitive Neuroscience, 16 papers in Materials Chemistry and 10 papers in Artificial Intelligence. Recurrent topics in Amanda Parker's work include Memory and Neural Mechanisms (16 papers), Machine Learning in Materials Science (13 papers) and Neural dynamics and brain function (9 papers). Amanda Parker is often cited by papers focused on Memory and Neural Mechanisms (16 papers), Machine Learning in Materials Science (13 papers) and Neural dynamics and brain function (9 papers). Amanda Parker collaborates with scholars based in United Kingdom, Australia and United States. Amanda Parker's co-authors include David Gaffan, Amanda S. Barnard, Alexander Easton, Edward L. Wilding, Timothy J. Bussey, Andrew M. Derrington, Fernand Gobet, Ben S. Webb, Nick E. Barraclough and Chris J. Tinsley and has published in prestigious journals such as Journal of Neuroscience, Applied Physics Letters and Journal of Applied Physics.

In The Last Decade

Amanda Parker

81 papers receiving 2.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Amanda Parker United Kingdom 26 1.3k 505 285 197 179 85 2.1k
Tony Stöcker Germany 33 1.3k 1.1× 316 0.6× 132 0.5× 250 1.3× 164 0.9× 117 3.3k
Kang Cheng Japan 22 1.7k 1.4× 220 0.4× 244 0.9× 115 0.6× 266 1.5× 71 2.4k
Andrew F. Rossi United States 16 2.0k 1.5× 812 1.6× 91 0.3× 129 0.7× 175 1.0× 24 2.6k
Kiyoshi Nakahara Japan 20 1.5k 1.2× 645 1.3× 88 0.3× 664 3.4× 147 0.8× 48 2.9k
Federico D’Agata Italy 33 2.3k 1.8× 330 0.7× 87 0.3× 193 1.0× 295 1.6× 83 4.2k
Matthias Schulz Germany 29 698 0.6× 668 1.3× 215 0.8× 504 2.6× 98 0.5× 116 2.8k
Vincent P. Ferrera United States 35 3.0k 2.4× 539 1.1× 291 1.0× 394 2.0× 284 1.6× 93 4.3k
Robert Trampel Germany 34 1.5k 1.2× 279 0.6× 59 0.2× 157 0.8× 172 1.0× 99 3.1k
John Strupp United States 21 2.1k 1.7× 228 0.5× 133 0.5× 126 0.6× 161 0.9× 33 4.1k
Seyed M. Mirsattari Canada 33 1.3k 1.0× 628 1.2× 292 1.0× 183 0.9× 69 0.4× 146 3.2k

Countries citing papers authored by Amanda Parker

Since Specialization
Citations

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

Fields of papers citing papers by Amanda Parker

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Amanda Parker

This figure shows the co-authorship network connecting the top 25 collaborators of Amanda Parker. A scholar is included among the top collaborators of Amanda Parker 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 Amanda Parker. Amanda Parker 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
1.
Pfeiffer, John R., Matthew Biancalana, Amanda Parker, et al.. (2024). Performance of an AI-powered visualization software platform for precision surgery in breast cancer patients. npj Breast Cancer. 10(1). 98–98. 1 indexed citations
2.
Parker, Amanda, et al.. (2024). Graph representation of multi-dimensional materials. Journal of Physics Materials. 7(2). 22005–22005.
3.
Barnard, Amanda S., et al.. (2024). Online meta-learned gradient norms for active learning in science and technology. Machine Learning Science and Technology. 5(1). 15041–15041. 2 indexed citations
4.
Parker, Amanda, et al.. (2023). Data-Driven Design of Classes of Ruthenium Nanoparticles Using Multitarget Bayesian Inference. Chemistry of Materials. 35(2). 728–738. 6 indexed citations
5.
Fischer, Julia, Amanda Parker, & Amanda S. Barnard. (2021). Interfacial informatics. Journal of Physics Materials. 4(4). 41001–41001. 3 indexed citations
6.
Parker, Amanda, Benyamin Motevalli, George Opletal, & Amanda S. Barnard. (2020). The pure and representative types of disordered platinum nanoparticles from machine learning. Nanotechnology. 32(9). 95404–95404. 11 indexed citations
7.
Motevalli, Benyamin, Amanda Parker, Baichuan Sun, & Amanda S. Barnard. (2019). The representative structure of graphene oxide nanoflakes from machine learning. Nano Futures. 3(4). 45001–45001. 35 indexed citations
8.
Parker, Amanda & Jörg Rottler. (2018). Entropic Network Model for Star Block Copolymer Thermoplastic Elastomers. Macromolecules. 51(23). 10021–10027. 7 indexed citations
9.
Lau, Annie, et al.. (2012). Comparative Usage of a Web-based Personally Controlled Health Management System and Normal Support: a Case Study in IVF. 7(2). 16. 9 indexed citations
10.
Parker, Amanda, Colin Blakemore, & Andrew M. Derrington. (2003). The Physiology of Cognitive Processes. Oxford University Press eBooks. 7 indexed citations
11.
Parker, Amanda. (2002). Structure, surfaces and shape: superficial and in-depth influences of Marr on visual physiology. Perception. 31. 2–2. 2 indexed citations
12.
Parker, Amanda, Mitch Waterman, & Angus Gellatly. (2000). Effect of environmental context manipulations on explicit and implicit memory for categorised and random words.. 19(1). 111–132. 9 indexed citations
13.
Parker, Amanda, Madeline J. Eacott, & David Gaffan. (1997). The Recognition Memory Deficit Caused by Mediodorsal Thalamic Lesion in Non‐human Primates: A Comparison with Rhinal Cortex Lesion. European Journal of Neuroscience. 9(11). 2423–2431. 62 indexed citations
14.
Cumming, Bruce G., et al.. (1995). THE CONTRIBUTION OF MOTION INFORMATION TO STEREO MATCHING - A STATISTICAL EFFICIENCY APPROACH. Investigative Ophthalmology & Visual Science. 36. 2 indexed citations
15.
Cumming, Bruce G., et al.. (1991). EFFECTS OF TEXTURE AND SHADING ON THE KDE. Investigative Ophthalmology & Visual Science. 32. 1277–1277. 4 indexed citations
16.
Hurlbert, Anya, Bruce G. Cumming, & Amanda Parker. (1991). CONSTRAINTS OF SPECULARITY MOTION ON GLOSSINESS AND ON SHAPE PERCEPTION. Perception. 20. 83–83. 3 indexed citations
17.
Christou, Chris, et al.. (1991). SHAPE-FROM-SHADING WITH MUTUAL ILLUMINATION. Investigative Ophthalmology & Visual Science. 32. 1180–1180. 3 indexed citations
18.
Hurlbert, Anya, Bruce G. Cumming, & Amanda Parker. (1991). RECOGNITION AND PERCEPTUAL USE OF SPECULAR REFLECTIONS. Investigative Ophthalmology & Visual Science. 32. 1278–1278. 18 indexed citations
19.
Parker, Amanda, et al.. (1988). MEASURES OF SURFACE SHAPE FROM DISPARITY FIELDS. Perception. 17. 365–366. 7 indexed citations
20.
Parker, Amanda, et al.. (1988). INVESTIGATION OF THE ORDERING CONSTRAINT IN HUMAN STEREO VISION. Perception. 17. 384–384. 4 indexed citations

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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