Bryant Wysocki

979 total citations
30 papers, 686 citations indexed

About

Bryant Wysocki is a scholar working on Electrical and Electronic Engineering, Artificial Intelligence and Cognitive Neuroscience. According to data from OpenAlex, Bryant Wysocki has authored 30 papers receiving a total of 686 indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Electrical and Electronic Engineering, 11 papers in Artificial Intelligence and 10 papers in Cognitive Neuroscience. Recurrent topics in Bryant Wysocki's work include Advanced Memory and Neural Computing (24 papers), Neural Networks and Reservoir Computing (10 papers) and Neural dynamics and brain function (8 papers). Bryant Wysocki is often cited by papers focused on Advanced Memory and Neural Computing (24 papers), Neural Networks and Reservoir Computing (10 papers) and Neural dynamics and brain function (8 papers). Bryant Wysocki collaborates with scholars based in United States, Qatar and India. Bryant Wysocki's co-authors include Nathan McDonald, Garrett S. Rose, Dhireesha Kudithipudi, Robinson E. Pino, Cory Merkel, Ramesh Karri, Miodrag Potkonjak, Yang Yi, Chenyuan Zhao and Jeyavijayan Rajendran and has published in prestigious journals such as Applied Physics Letters, Proceedings of the IEEE and Frontiers in Neuroscience.

In The Last Decade

Bryant Wysocki

29 papers receiving 659 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Bryant Wysocki United States 15 633 292 259 164 133 30 686
Nathan McDonald United States 14 782 1.2× 385 1.3× 280 1.1× 149 0.9× 128 1.0× 35 867
Rawan Naous Saudi Arabia 12 777 1.2× 171 0.6× 162 0.6× 135 0.8× 110 0.8× 21 851
Kyung Seok Woo South Korea 14 518 0.8× 159 0.5× 72 0.3× 171 1.0× 112 0.8× 26 562
F. Merrikh Bayat United States 13 1.2k 1.9× 535 1.8× 109 0.4× 240 1.5× 235 1.8× 17 1.2k
Harika Manem United States 12 542 0.9× 313 1.1× 99 0.4× 48 0.3× 46 0.3× 18 549
Roberto Carboni Italy 13 953 1.5× 436 1.5× 70 0.3× 145 0.9× 243 1.8× 16 1.0k
Dhireesha Kudithipudi United States 14 625 1.0× 132 0.5× 74 0.3× 332 2.0× 202 1.5× 88 732
Bo Marr United States 6 438 0.7× 90 0.3× 72 0.3× 158 1.0× 92 0.7× 11 490
Nimrod Wald Israel 13 1.7k 2.7× 915 3.1× 196 0.8× 134 0.8× 95 0.7× 14 1.8k
Beiye Liu United States 13 754 1.2× 217 0.7× 65 0.3× 223 1.4× 82 0.6× 24 788

Countries citing papers authored by Bryant Wysocki

Since Specialization
Citations

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

Fields of papers citing papers by Bryant Wysocki

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bryant Wysocki

This figure shows the co-authorship network connecting the top 25 collaborators of Bryant Wysocki. A scholar is included among the top collaborators of Bryant Wysocki 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 Bryant Wysocki. Bryant Wysocki 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.
Zhao, Chenyuan, et al.. (2019). Energy Efficient Temporal Spatial Information Processing Circuits Based on STDP and Spike Iteration. IEEE Transactions on Circuits & Systems II Express Briefs. 67(10). 1715–1719. 6 indexed citations
2.
Shafin, Rubayet, Lingjia Liu, Jonathan Ashdown, et al.. (2018). Realizing Green Symbol Detection via Reservoir Computing: An Energy-Efficiency Perspective. 3. 1–6. 12 indexed citations
3.
Merkel, Cory, Dhireesha Kudithipudi, Manan Suri, & Bryant Wysocki. (2017). Stochastic CBRAM-Based Neuromorphic Time Series Prediction System. ACM Journal on Emerging Technologies in Computing Systems. 13(3). 1–14. 4 indexed citations
4.
Kudithipudi, Dhireesha, et al.. (2016). Design and Analysis of a Neuromemristive Reservoir Computing Architecture for Biosignal Processing. Frontiers in Neuroscience. 9. 502–502. 74 indexed citations
5.
Zhao, Chenyuan, Bryant Wysocki, Nathan McDonald, et al.. (2016). Energy Efficient Spiking Temporal Encoder Design for Neuromorphic Computing Systems. 2(4). 265–276. 26 indexed citations
6.
Zhao, Chenyuan, et al.. (2015). Neuromorphic encoding system design with chaos based CMOS analog neuron. 1–6. 15 indexed citations
7.
Zhao, Chenyuan, et al.. (2015). Spike-Time-Dependent Encoding for Neuromorphic Processors. ACM Journal on Emerging Technologies in Computing Systems. 12(3). 1–21. 32 indexed citations
8.
Merkel, Cory, et al.. (2015). Design and analysis of neuromemristive echo state networks with limited-precision synapses. 2. 1–6. 6 indexed citations
9.
Yang, Wei, et al.. (2014). Autonomous target tracking of UAVs based on low-power neural network hardware. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 9119. 91190P–91190P. 3 indexed citations
10.
Rose, Garrett S., et al.. (2013). A write-time based memristive PUF for hardware security applications. International Conference on Computer Aided Design. 830–833. 44 indexed citations
11.
Liu, Beiye, Yiran Chen, Bryant Wysocki, & Tingwen Huang. (2013). Reconfigurable Neuromorphic Computing System with Memristor-Based Synapse Design. Neural Processing Letters. 41(2). 159–167. 19 indexed citations
12.
Feng, Ji, et al.. (2013). Memristor-based synapse design and a case study in reconfigurable systems. 1–6. 2 indexed citations
13.
Rose, Garrett S., et al.. (2013). Foundations of memristor based PUF architectures. 52–57. 58 indexed citations
14.
Chen, Zhijie, et al.. (2013). A compact modeling of TiO2-TiO2–x memristor. Applied Physics Letters. 102(15). 37 indexed citations
15.
Li, Hai, et al.. (2012). Spintronic devices: From memory to memristor. 159. 1–4. 1 indexed citations
16.
Pino, Robinson E., et al.. (2011). Compact Method for Modeling and Simulation of Memristor Devices. 6 indexed citations
17.
18.
Pino, Robinson E., et al.. (2010). Compact method for modeling and simulation of memristor devices: Ion conductor chalcogenide-based memristor devices. Scholar Works (Boise State University). 1–4. 47 indexed citations
19.
Wysocki, Bryant & Michael A. Marciniak. (2007). Discrimination between electronic and optical blooming in an InSb focal-plane array under high-intensity excitation. Infrared Physics & Technology. 51(3). 137–145. 14 indexed citations
20.
Brown, Kevin, et al.. (2007). Control over spectral content via differential pumping of a monolithic passively mode-locked quantum dot laser. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6572. 65720A–65720A.

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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