Steven K. Esser
- Electrical and Electronic Engineering top 1%
- Cognitive Neuroscience top 1%
- Cellular and Molecular Neuroscience top 1%
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 5%
- Co-authors
- Dharmendra S. ModhaJohn V. ArthurRathinakumar AppuswamyPaul MerollaAndrew S. CassidyMyron FlicknerBrian TabaArnon Amir
- Topics
- Advanced Memory and Neural Computing (8 papers)Neural dynamics and brain function (6 papers)Photoreceptor and optogenetics research (3 papers)
- Cited by
- Cognitive NeuroscienceCellular and Molecular NeuroscienceElectrical and Electronic Engineering
- Partner nations
- United StatesSwitzerlandIndia
In The Last Decade
Steven K. Esser
12 papers receiving 4.3k citations
Hit Papers
Peers
Comparison fields: 5 of 128
- Electrical and Electronic Engineering 3.6k
- Cognitive Neuroscience 1.6k
- Cellular and Molecular Neuroscience 1.5k
- Artificial Intelligence 1.3k
- Computer Vision and Pattern Recognition 244
Countries citing papers authored by Steven K. Esser
This map shows the geographic impact of Steven K. Esser'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 Steven K. Esser with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steven K. Esser more than expected).
Fields of papers citing papers by Steven K. Esser
This network shows the impact of papers produced by Steven K. Esser. 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 Steven K. Esser. The network helps show where Steven K. Esser may publish in the future.
Co-authorship network of co-authors of Steven K. Esser
This figure shows the co-authorship network connecting the top 25 collaborators of Steven K. Esser. A scholar is included among the top collaborators of Steven K. Esser 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 Steven K. Esser. Steven K. Esser is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | LEARNED STEP SIZE QUANTIZATION | 38 |
| 2 | 21 | |
| 3 | Convolutional networks for fast, energy-efficient neuromorphic computingbreakdown → | 482 |
| 4 | 12 | |
| 5 | A million spiking-neuron integrated circuit with a scalable communication network and interfacebreakdown → | 2780 |
| 6 | 103 | |
| 7 | 65 | |
| 8 | 264 | |
| 9 | 200 | |
| 10 | 175 | |
| 11 | 9 | |
| 12 | 284 |
About Steven K. Esser
Steven K. Esser is a scholar working on Cellular and Molecular Neuroscience, Cognitive Neuroscience and Anesthesiology and Pain Medicine, having authored 12 papers that have together received 4.4k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (8 papers), Neural dynamics and brain function (6 papers) and Photoreceptor and optogenetics research (3 papers). The work is most often cited by research in Cognitive Neuroscience (1.6k citations), Cellular and Molecular Neuroscience (1.5k citations) and Electrical and Electronic Engineering (3.6k citations). Steven K. Esser has collaborated with scholars based in United States, Switzerland and India. Frequent co-authors include Dharmendra S. Modha, John V. Arthur, Rathinakumar Appuswamy, Paul Merolla, Andrew S. Cassidy, Myron Flickner, Brian Taba, Arnon Amir, Bernard Brezzo and W. P. Risk. Their work appears in journals such as Science, Proceedings of the National Academy of Sciences and Communications of the ACM.
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.