Viktor Prasanna

453 total citations
29 papers, 172 citations indexed

About

Viktor Prasanna is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Viktor Prasanna has authored 29 papers receiving a total of 172 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 10 papers in Electrical and Electronic Engineering and 8 papers in Computer Vision and Pattern Recognition. Recurrent topics in Viktor Prasanna's work include Advanced Neural Network Applications (4 papers), Advanced Graph Neural Networks (4 papers) and Adversarial Robustness in Machine Learning (3 papers). Viktor Prasanna is often cited by papers focused on Advanced Neural Network Applications (4 papers), Advanced Graph Neural Networks (4 papers) and Adversarial Robustness in Machine Learning (3 papers). Viktor Prasanna collaborates with scholars based in United States. Viktor Prasanna's co-authors include Yi-Hua E. Yang, Bo Hong, Rajgopal Kannan, Hanqing Zeng, Hongkuan Zhou, Ajitesh Srivastava, Bingyi Zhang, Yuan Meng, Ananthram Swami and Ajey P. Jacob and has published in prestigious journals such as IEEE Transactions on Computers, IEEE Transactions on Parallel and Distributed Systems and Proceedings of the VLDB Endowment.

In The Last Decade

Viktor Prasanna

24 papers receiving 169 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Viktor Prasanna United States 5 89 71 64 32 30 29 172
Petr Švenda Czechia 8 104 1.2× 55 0.8× 22 0.3× 18 0.6× 42 1.4× 43 181
Medha Atre United States 7 126 1.4× 118 1.7× 68 1.1× 67 2.1× 72 2.4× 14 233
Moriyoshi Ohara Japan 8 63 0.7× 175 2.5× 41 0.6× 25 0.8× 58 1.9× 20 270
S. W. Song Brazil 7 82 0.9× 100 1.4× 81 1.3× 25 0.8× 37 1.2× 25 201
Paweł Morawiecki Poland 8 117 1.3× 25 0.4× 31 0.5× 29 0.9× 76 2.5× 24 174
Barış Ege Netherlands 7 123 1.4× 23 0.3× 86 1.3× 86 2.7× 36 1.2× 10 188
Coleman Hooper United States 6 92 1.0× 41 0.6× 46 0.7× 92 2.9× 52 1.7× 11 215
Mehmet E. Belviranlı United States 11 41 0.5× 166 2.3× 171 2.7× 39 1.2× 69 2.3× 26 268
Andy Yoo United States 8 42 0.5× 146 2.1× 108 1.7× 37 1.2× 48 1.6× 16 219
Weikang Qiao United States 10 68 0.8× 165 2.3× 193 3.0× 118 3.7× 29 1.0× 15 296

Countries citing papers authored by Viktor Prasanna

Since Specialization
Citations

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

Fields of papers citing papers by Viktor Prasanna

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Viktor Prasanna

This figure shows the co-authorship network connecting the top 25 collaborators of Viktor Prasanna. A scholar is included among the top collaborators of Viktor Prasanna 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 Viktor Prasanna. Viktor Prasanna 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.
Prasanna, Viktor, et al.. (2025). Scalable in-memory compute optical processor. 45–45. 1 indexed citations
2.
3.
4.
Jacob, Ajey P., et al.. (2024). Predictive Performance of Photonic SRAM-Based in-Memory Computing for Tensor Decomposition. 1–5. 1 indexed citations
5.
Zeng, Hanqing, et al.. (2024). TASER: Temporal Adaptive Sampling for Fast and Accurate Dynamic Graph Representation Learning. 926–937. 4 indexed citations
6.
Zhang, Bingyi, et al.. (2024). ViTeGNN: Towards Versatile Inference of Temporal Graph Neural Networks on FPGA. IEEE Transactions on Parallel and Distributed Systems. 36(3). 502–519. 1 indexed citations
7.
Lin, Yi-Chien, Zhijie Xu, & Viktor Prasanna. (2024). xBS-GNN: Accelerating Billion-Scale GNNTraining on FPGA. 659–666. 1 indexed citations
8.
Zhang, Bingyi, et al.. (2024). GCV-Turbo: End-to-end Acceleration of GNN-based Computer Vision Tasks on FPGA. 66–77. 1 indexed citations
9.
Li, Shouyi, et al.. (2024). Accelerating ViT Inference on FPGA through Static and Dynamic Pruning. 78–89. 1 indexed citations
10.
Zhang, Bingyi, Hanqing Zeng, & Viktor Prasanna. (2022). Low-latency Mini-batch GNN Inference on CPU-FPGA Heterogeneous Platform. 11–21. 9 indexed citations
11.
Kannan, Rajgopal, et al.. (2022). Throughput optimization in heterogeneous MIMO networks. 42–47. 2 indexed citations
12.
Meng, Yuan, Rajgopal Kannan, & Viktor Prasanna. (2022). Accelerating Monte-Carlo Tree Search on CPU-FPGA Heterogeneous Platform. 176–182. 3 indexed citations
13.
Meng, Yuan, et al.. (2022). Accelerator Design and Exploration for Deformable Convolution Networks. 1–6. 3 indexed citations
14.
Jaiswal, Akhilesh, et al.. (2022). Performance Modeling Sparse MTTKRP Using Optical Static Random Access Memory on FPGA. 1–7. 1 indexed citations
15.
Petrini, Fabrizio, et al.. (2022). Accelerating Prefix Scan with in-network computing on Intel PIUMA. 3. 59–68. 1 indexed citations
16.
Zhang, Bingyi, et al.. (2022). Modeling the Energy Efficiency of GEMM using Optical Random Access Memory. 1–7. 1 indexed citations
17.
Petrini, Fabrizio, et al.. (2021). In-network reductions on multi-dimensional HyperX. 1–8. 4 indexed citations
18.
Zhou, Hongkuan, Ajitesh Srivastava, Hanqing Zeng, Rajgopal Kannan, & Viktor Prasanna. (2021). Accelerating large scale real-time GNN inference using channel pruning. Proceedings of the VLDB Endowment. 14(9). 1597–1605. 35 indexed citations
19.
Hong, Bo & Viktor Prasanna. (2007). Adaptive Allocation of Independent Tasks to Maximize Throughput. IEEE Transactions on Parallel and Distributed Systems. 18(10). 1420–1435. 26 indexed citations
20.
Singh, Manbir, et al.. (2006). Acceleration of Fiber Tracking in DTI Tractography by Reconfigurable Computer Hardware. PubMed. 2006. 4819–4822. 1 indexed citations

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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