Alex H. Williams
- Cognitive Neuroscience top 5%
- Cellular and Molecular Neuroscience top 10%
- Molecular Biology
- Artificial Intelligence
- Electrical and Electronic Engineering
- Co-authors
- Timothy O’LearyEve MarderJonathan S. CaplanKrishna V. ShenoyStephen I. RyuSurya GanguliTony Hyun KimSaurabh Vyas
- Topics
- Neural dynamics and brain function (8 papers)Neuroscience and Neuropharmacology Research (4 papers)Memory and Neural Mechanisms (4 papers)
- Partner nations
- United StatesGermanyUnited Kingdom
In The Last Decade
Alex H. Williams
17 papers receiving 507 citations
Peers
Comparison fields: 5 of 83
- Cognitive Neuroscience 324
- Cellular and Molecular Neuroscience 253
- Molecular Biology 110
- Artificial Intelligence 57
- Electrical and Electronic Engineering 44
Countries citing papers authored by Alex H. Williams
This map shows the geographic impact of Alex H. Williams'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 Alex H. Williams with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alex H. Williams more than expected).
Fields of papers citing papers by Alex H. Williams
This network shows the impact of papers produced by Alex H. Williams. 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 Alex H. Williams. The network helps show where Alex H. Williams may publish in the future.
Co-authorship network of co-authors of Alex H. Williams
This figure shows the co-authorship network connecting the top 25 collaborators of Alex H. Williams. A scholar is included among the top collaborators of Alex H. Williams 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 Alex H. Williams. Alex H. Williams is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 3 | |
| 4 | 2 | |
| 5 | 6 | |
| 6 | 2 | |
| 7 | 1 | |
| 8 | 23 | |
| 9 | 4 | |
| 10 | 55 | |
| 11 | 47 | |
| 12 | 154 | |
| 13 | Learning Dynamics of Deep Networks Admit Low-Rank Tensor Descriptions | 0 |
| 14 | 29 | |
| 15 | 18 | |
| 16 | 133 | |
| 17 | 12 | |
| 18 | 19 |
About Alex H. Williams
Alex H. Williams is a scholar working on Computational Mathematics, Developmental Biology and Cognitive Neuroscience, having authored 18 papers that have together received 512 indexed citations. Recurring topics across this work include Neural dynamics and brain function (8 papers), Neuroscience and Neuropharmacology Research (4 papers) and Memory and Neural Mechanisms (4 papers). The work is most often cited by research in Computational Mathematics (37 citations), Cognitive Neuroscience (324 citations) and Cellular and Molecular Neuroscience (253 citations). Alex H. Williams has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Timothy O’Leary, Eve Marder, Jonathan S. Caplan, Krishna V. Shenoy, Stephen I. Ryu, Surya Ganguli, Tony Hyun Kim, Saurabh Vyas, Tamara G. Kolda and Mark J. Schnitzer. Their work appears in journals such as Nature, Proceedings of the National Academy of Sciences and Neuron.
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.