Chad Giusti

1.6k citations
17 papers · 756 · h-index 9

Impact in

Papers in

Chad Giusti

16 papers receiving 733 citations

Peers

Chad Giusti
Comparison fields: 5 of 97
  • Cognitive Neuroscience 311
  • Computational Theory and Mathematics 270
  • Statistical and Nonlinear Physics 175
  • Biophysics 52
  • Computational Mathematics 3
Replace Carina Curto with:
Carina Curto United States
Martina Scolamiero Sweden
Katharine Turner Australia
Benedetta Franceschiello Switzerland
Michael Reimann Switzerland
Alice Patania United States
Mukund Balasubramanian United States
Minh Tang United States
Max Nolte Switzerland
Giuseppe Chindemi Switzerland
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Citations per field
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Citations per year

Countries citing papers authored by Chad Giusti

Since Specialization
Citations

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

Fields of papers citing papers by Chad Giusti

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

17 of 17 papers shown
#Work
1 2016271
2 2015211
3 2016100
4 201854
5 201636
6 201922
7 201813
8 201413
9 20219
10 20126
11 20235
12 20124
13 20234
14
Structural drivers of diverse neural dynamics and their evolution across development
20163
15 20203
16 20241
17 20131

About Chad Giusti

Chad Giusti is a scholar working on Computational Theory and Mathematics, Mathematical Physics, Cognitive Neuroscience, Molecular Biology and Radiology, Nuclear Medicine and Imaging, having authored 17 papers that have together received 756 indexed citations. Recurring topics across this work include Topological and Geometric Data Analysis (11 papers), Homotopy and Cohomology in Algebraic Topology (6 papers), Neural dynamics and brain function (4 papers), Alzheimer's disease research and treatments (2 papers), Advanced Neuroimaging Techniques and Applications (2 papers), Memory and Neural Mechanisms (2 papers), Functional Brain Connectivity Studies (2 papers) and Cell Image Analysis Techniques (2 papers). The work is most often cited by research in Cognitive Neuroscience (311 citations), Computational Theory and Mathematics (270 citations), Statistical and Nonlinear Physics (175 citations), Biophysics (52 citations) and Computational Mathematics (3 citations). Chad Giusti has collaborated with scholars based in United States, United Kingdom and Slovakia. Frequent co-authors include Danielle S. Bassett, Robert Ghrist, Vladimir Itskov, Carina Curto, Eva Pastalkova, Kelvin O. Lim, Qawi K. Telesford, Ann E. Sizemore, Elisabeth A. Karuza and Karen E. Daniels. Their work appears in journals such as BMC Neuroscience, Nature Human Behaviour, Neural Computation, Journal of Topology and Journal of Computational Neuroscience.

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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