Sakyasingha Dasgupta

907 total citations
21 papers, 408 citations indexed

About

Sakyasingha Dasgupta is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Cognitive Neuroscience. According to data from OpenAlex, Sakyasingha Dasgupta has authored 21 papers receiving a total of 408 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 8 papers in Computer Vision and Pattern Recognition and 7 papers in Cognitive Neuroscience. Recurrent topics in Sakyasingha Dasgupta's work include Neural dynamics and brain function (7 papers), Neural Networks and Reservoir Computing (6 papers) and Advanced Memory and Neural Computing (6 papers). Sakyasingha Dasgupta is often cited by papers focused on Neural dynamics and brain function (7 papers), Neural Networks and Reservoir Computing (6 papers) and Advanced Memory and Neural Computing (6 papers). Sakyasingha Dasgupta collaborates with scholars based in Germany, Denmark and Japan. Sakyasingha Dasgupta's co-authors include Poramate Manoonpong, Florentin Wörgötter, Yiyu Shi, Weiwen Jiang, Takayuki Osogami, Lei Yang, Jingtong Hu, Dennis Goldschmidt, Qingfeng Zhuge and Edwin H.‐M. Sha and has published in prestigious journals such as Scientific Reports, Information Sciences and IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems.

In The Last Decade

Sakyasingha Dasgupta

20 papers receiving 398 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sakyasingha Dasgupta Germany 11 154 138 123 85 72 21 408
Bernard Girau France 9 200 1.3× 240 1.7× 68 0.6× 128 1.5× 74 1.0× 62 448
Kofi Appiah United Kingdom 14 149 1.0× 136 1.0× 320 2.6× 49 0.6× 73 1.0× 52 572
Haowen Fang United States 11 148 1.0× 260 1.9× 80 0.7× 84 1.0× 25 0.3× 26 467
Mokhtar Nibouche United Kingdom 9 86 0.6× 142 1.0× 102 0.8× 91 1.1× 28 0.4× 55 389
Benoît Miramond France 11 127 0.8× 248 1.8× 94 0.8× 100 1.2× 21 0.3× 39 436
Enea Ceolini Switzerland 12 318 2.1× 197 1.4× 124 1.0× 255 3.0× 76 1.1× 27 826
Haina Rong China 15 194 1.3× 269 1.9× 86 0.7× 43 0.5× 29 0.4× 50 971
César Torres-Huitzil Mexico 15 159 1.0× 371 2.7× 263 2.1× 106 1.2× 113 1.6× 82 737
Scott Koziol United States 13 93 0.6× 329 2.4× 85 0.7× 116 1.4× 152 2.1× 43 501

Countries citing papers authored by Sakyasingha Dasgupta

Since Specialization
Citations

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

Fields of papers citing papers by Sakyasingha Dasgupta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sakyasingha Dasgupta

This figure shows the co-authorship network connecting the top 25 collaborators of Sakyasingha Dasgupta. A scholar is included among the top collaborators of Sakyasingha Dasgupta 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 Sakyasingha Dasgupta. Sakyasingha Dasgupta 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.
Dasgupta, Sakyasingha, et al.. (2021). Dynamic Neural Accelerator for Reconfigurable & Energy-efficient Neural Network Inference. 1–21. 1 indexed citations
2.
Jiang, Weiwen, Bingbing Li, Qingfeng Zhuge, et al.. (2021). Dancing along Battery: Enabling Transformer with Run-time Reconfigurability on Mobile Devices. 1003–1008. 13 indexed citations
3.
Lu, Qing, Weiwen Jiang, Meng Jiang, et al.. (2021). FGNAS: FPGA-Aware Graph Neural Architecture Search. 3 indexed citations
4.
Jiang, Weiwen, Lei Yang, Edwin H.‐M. Sha, et al.. (2020). Hardware/Software Co-Exploration of Neural Architectures. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 39(12). 4805–4815. 98 indexed citations
5.
Jiang, Weiwen, Lei Yang, Sakyasingha Dasgupta, Jingtong Hu, & Yiyu Shi. (2020). Standing on the Shoulders of Giants: Hardware and Neural Architecture Co-Search With Hot Start. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 39(11). 4154–4165. 47 indexed citations
6.
Goldschmidt, Dennis, Poramate Manoonpong, & Sakyasingha Dasgupta. (2017). A Neurocomputational Model of Goal-Directed Navigation in Insect-Inspired Artificial Agents. Frontiers in Neurorobotics. 11. 20–20. 24 indexed citations
7.
Dasgupta, Sakyasingha, et al.. (2017). Text to image generative model using constrained embedding space mapping. 1–6. 6 indexed citations
8.
Dasgupta, Sakyasingha & Takayuki Osogami. (2017). Nonlinear Dynamic Boltzmann Machines for Time-Series Prediction. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 45 indexed citations
9.
Dasgupta, Sakyasingha, et al.. (2016). Efficient Signal Processing in Random Networks that Generate Variability: A Comparison of Internally Generated and Externally Induced Variability. APS March Meeting Abstracts. 2016. 1 indexed citations
10.
Tetzlaff, Christian, Sakyasingha Dasgupta, Tomas Kulvičius, & Florentin Wörgötter. (2015). The Use of Hebbian Cell Assemblies for Nonlinear Computation. Scientific Reports. 5(1). 12866–12866. 23 indexed citations
11.
Dasgupta, Sakyasingha, Dennis Goldschmidt, Florentin Wörgötter, & Poramate Manoonpong. (2015). Distributed recurrent neural forward models with synaptic adaptation and CPG-based control for complex behaviors of walking robots. Frontiers in Neurorobotics. 9. 10–10. 30 indexed citations
12.
Dasgupta, Sakyasingha, Christian Tetzlaff, Tomas Kulvičius, & Florentin Wörgötter. (2015). Self-organization of computation in neural systems by interaction between homeostatic and synaptic plasticity. BMC Neuroscience. 16(S1). 1 indexed citations
13.
Dasgupta, Sakyasingha, et al.. (2014). Neuromodulatory adaptive combination of correlation-based learning in cerebellum and reward-based learning in basal ganglia for goal-directed behavior control. Frontiers in Neural Circuits. 8. 126–126. 23 indexed citations
14.
Chen, Weihai, et al.. (2014). Multiple chaotic central pattern generators with learning for legged locomotion and malfunction compensation. Information Sciences. 294. 666–682. 36 indexed citations
15.
Dasgupta, Sakyasingha, Poramate Manoonpong, & Florentin Wörgötter. (2014). Reservoir of neurons with adaptive time constants: a hybrid model for robust motor-sensory temporal processing. BMC Neuroscience. 15(S1). 1 indexed citations
16.
Manoonpong, Poramate, Sakyasingha Dasgupta, Dennis Goldschmidt, & Florentin Wörgötter. (2014). Reservoir-based online adaptive forward models with neural control for complex locomotion in a hexapod robot. University of Southern Denmark Research Portal (University of Southern Denmark). 3295–3302. 10 indexed citations
17.
Dasgupta, Sakyasingha, Florentin Wörgötter, Jun Morimoto, & Poramate Manoonpong. (2013). Neural Combinatorial Learning of Goal-Directed Behavior with Reservoir Critic and Reward Modulated Hebbian Plasticity. 304. 993–1000. 3 indexed citations
18.
Dasgupta, Sakyasingha, Florentin Wörgötter, & Poramate Manoonpong. (2013). Information dynamics based self-adaptive reservoir for delay temporal memory tasks. Evolving Systems. 4(4). 235–249. 28 indexed citations
19.
20.
Bartlett, Peter L. & Sakyasingha Dasgupta. (2002). Exponential convergence of a gradient descent algorithm for a class of recurrent neural networks. 1. 497–500.

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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