Jun Sawada

6.7k citations
9 papers · 4.3k · 2 hit papers · h-index 8

Impact in

Papers in

Jun Sawada

9 papers receiving 4.2k citations

Jun Sawada's Hit Papers

TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip 2015 · 1.1k citations
1.1k0+4+8Years since publication50010001.5k2.0k2.5k

Peers

Jun Sawada
Comparison fields: 5 of 93
  • Cellular and Molecular Neuroscience 1.4k
  • Cognitive Neuroscience 1.3k
  • Electrical and Electronic Engineering 3.9k
  • Artificial Intelligence 1.3k
  • Hardware and Architecture 114
Replace Filipp Akopyan with:
Filipp Akopyan United States
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Citations per field
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Citations per year

Countries citing papers authored by Jun Sawada

Since Specialization
Citations

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

Fields of papers citing papers by Jun Sawada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1
A million spiking-neuron integrated circuit with a scalable communication network and interface
Hit paper breakdown →
20142852
2
TrueNorth: Design and Tool Flow of a 65 mW 1 Million Neuron Programmable Neurosynaptic Chip
Hit paper breakdown →
20151098
3 2013171
4 2007105
5 200516
6 200616
7 200314
8
TrueNorth: A High-Performance, Low-Power Neurosynaptic Processor for Multi-Sensory Perception, Action, and Cognition
201612
9 20061

About Jun Sawada

Jun Sawada is a scholar working on Electrical and Electronic Engineering, Cognitive Neuroscience, Biomedical Engineering, Cellular and Molecular Neuroscience and Artificial Intelligence, having authored 9 papers that have together received 4.3k indexed citations. Recurring topics across this work include Advanced Memory and Neural Computing (4 papers), Low-power high-performance VLSI design (3 papers), Neural dynamics and brain function (3 papers), Analog and Mixed-Signal Circuit Design (3 papers), Neuroscience and Neural Engineering (2 papers), Neural Networks and Applications (2 papers), Numerical Methods and Algorithms (2 papers) and Interconnection Networks and Systems (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (1.4k citations), Cognitive Neuroscience (1.3k citations), Electrical and Electronic Engineering (3.9k citations), Artificial Intelligence (1.3k citations) and Hardware and Architecture (114 citations). Jun Sawada has collaborated with scholars based in United States and Japan. Frequent co-authors include John V. Arthur, Filipp Akopyan, Rodrigo Alvarez-Icaza, Dharmendra S. Modha, Paul Merolla, Andrew S. Cassidy, Bryan L. Jackson, W. P. Risk, Rajit Manohar and Bernard Brezzo. Their work appears in journals such as Science, IBM Journal of Research and Development and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

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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