Guohao Dai

784 total citations
46 papers, 432 citations indexed

About

Guohao Dai is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Guohao Dai has authored 46 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Computer Vision and Pattern Recognition, 20 papers in Artificial Intelligence and 17 papers in Electrical and Electronic Engineering. Recurrent topics in Guohao Dai's work include Advanced Memory and Neural Computing (12 papers), Advanced Neural Network Applications (10 papers) and Ferroelectric and Negative Capacitance Devices (8 papers). Guohao Dai is often cited by papers focused on Advanced Memory and Neural Computing (12 papers), Advanced Neural Network Applications (10 papers) and Ferroelectric and Negative Capacitance Devices (8 papers). Guohao Dai collaborates with scholars based in China, United States and Hong Kong. Guohao Dai's co-authors include Yu Wang, Huazhong Yang, Zhenhua Zhu, Huazhong Yang, Guyue Huang, Hanbo Sun, Yu Wang, Lixue Xia, Shulin Zeng and Song Han and has published in prestigious journals such as IEEE Transactions on Computers, IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems and ACM Transactions on Reconfigurable Technology and Systems.

In The Last Decade

Guohao Dai

39 papers receiving 427 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Guohao Dai China 10 199 160 157 113 84 46 432
Bharat Kaul United States 10 278 1.4× 269 1.7× 184 1.2× 208 1.8× 120 1.4× 18 577
Olivier Giroux United States 6 115 0.6× 83 0.5× 137 0.9× 162 1.4× 117 1.4× 10 404
Zheng Qu United States 9 114 0.6× 120 0.8× 137 0.9× 65 0.6× 59 0.7× 17 294
Eric Qin United States 8 252 1.3× 144 0.9× 125 0.8× 188 1.7× 116 1.4× 11 459
Jiawen Liu China 12 102 0.5× 74 0.5× 128 0.8× 112 1.0× 84 1.0× 30 335
Andrew Lukefahr United States 8 217 1.1× 232 1.4× 178 1.1× 275 2.4× 190 2.3× 15 539
Xuechao Wei China 10 321 1.6× 286 1.8× 143 0.9× 182 1.6× 113 1.3× 28 566
Xuan Yang United States 9 385 1.9× 292 1.8× 149 0.9× 257 2.3× 131 1.6× 18 640
Shengyuan Zhou China 8 213 1.1× 173 1.1× 122 0.8× 95 0.8× 51 0.6× 14 378
Sitao Huang United States 12 143 0.7× 132 0.8× 137 0.9× 144 1.3× 108 1.3× 32 421

Countries citing papers authored by Guohao Dai

Since Specialization
Citations

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

Fields of papers citing papers by Guohao Dai

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Guohao Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Guohao Dai. A scholar is included among the top collaborators of Guohao Dai 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 Guohao Dai. Guohao Dai 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
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Zeng, Shulin, Zhenhua Zhu, Xuefei Ning, et al.. (2025). FMC-LLM: Enabling FPGAs for Efficient Batched Decoding of 70B+ LLMs with a Memory-Centric Streaming Architecture. 55–55. 1 indexed citations
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Zhong, Kai, Shulin Zeng, Zhenhua Zhu, et al.. (2024). DySpMM: From Fix to Dynamic for Sparse Matrix-Matrix Multiplication Accelerators. 1–6.
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Zhong, Kai, Zhenhua Zhu, Guohao Dai, et al.. (2024). FEASTA: A Flexible and Efficient Accelerator for Sparse Tensor Algebra in Machine Learning. 349–366. 4 indexed citations
8.
Zeng, Shulin, et al.. (2024). FlightLLM: Efficient Large Language Model Inference with a Complete Mapping Flow on FPGAs. 223–234. 49 indexed citations
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Zeng, Shulin, Zhenhua Zhu, Guohao Dai, et al.. (2023). DF-GAS: a Distributed FPGA-as-a-Service Architecture towards Billion-Scale Graph-based Approximate Nearest Neighbor Search. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 283–296. 9 indexed citations
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Tang, Haotian, et al.. (2023). TorchSparse++: Efficient Training and Inference Framework for Sparse Convolution on GPUs. 225–239. 12 indexed citations
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Cen, Yukuo, Zhenyu Hou, Qibin Chen, et al.. (2023). CogDL: A Comprehensive Library for Graph Deep Learning. 747–758. 9 indexed citations
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Li, Shiyao, Zhenhua Zhu, Jiangwei Zhang, et al.. (2023). Memory-Efficient and Real-Time SPAD-based dToF Depth Sensor with Spatial and Statistical Correlation. 1–6. 1 indexed citations
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Liu, Jun, Zhenhua Zhu, Hanbo Sun, et al.. (2022). Optimizing Graph-based Approximate Nearest Neighbor Search: Stronger and Smarter. 179–184. 2 indexed citations
14.
Zhong, Kai, Xuefei Ning, Guohao Dai, et al.. (2022). Exploring the Potential of Low-Bit Training of Convolutional Neural Networks. IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems. 41(12). 5421–5434. 7 indexed citations
15.
Wang, Yitu, Zhenhua Zhu, Guohao Dai, et al.. (2021). Rerec: In-ReRAM Acceleration with Access-Aware Mapping for Personalized Recommendation. 1–9. 18 indexed citations
16.
Zeng, Shulin, Guohao Dai, Hanbo Sun, et al.. (2021). A Unified FPGA Virtualization Framework for General-Purpose Deep Neural Networks in the Cloud. ACM Transactions on Reconfigurable Technology and Systems. 15(3). 1–31. 3 indexed citations
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Yu, Jincheng, Zhilin Xu, Shulin Zeng, et al.. (2020). INCA: INterruptible CNN Accelerator for Multi-tasking in Embedded Robots. 1–6. 6 indexed citations
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Zhu, Zhenhua, Hanbo Sun, Yujun Lin, et al.. (2019). A Configurable Multi-Precision CNN Computing Framework Based on Single Bit RRAM. 1–6. 67 indexed citations
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Li, Yubin, et al.. (2016). Approximate Frequent Itemset Mining for streaming data on FPGA. 126. 1–4. 3 indexed citations
20.
Li, Yubin, Guohao Dai, Yuzhi Wang, et al.. (2015). A self-aware data compression system on FPGA in Hadoop. 7. 196–199. 6 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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Breakdown of academic impact, for papers by Bharat Kaul Breakdown of academic impact, for papers by Olivier Giroux Breakdown of academic impact, for papers by Zheng Qu Breakdown of academic impact, for papers by Eric Qin Breakdown of academic impact, for papers by Jiawen Liu Breakdown of academic impact, for papers by Andrew Lukefahr Breakdown of academic impact, for papers by Xuechao Wei Breakdown of academic impact, for papers by Xuan Yang Breakdown of academic impact, for papers by Shengyuan Zhou Breakdown of academic impact, for papers by Sitao Huang
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