Linghao Song

2.9k total citations · 1 hit paper
40 papers, 1.7k citations indexed

About

Linghao Song is a scholar working on Electrical and Electronic Engineering, Computer Vision and Pattern Recognition and Artificial Intelligence. According to data from OpenAlex, Linghao Song has authored 40 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Electrical and Electronic Engineering, 18 papers in Computer Vision and Pattern Recognition and 13 papers in Artificial Intelligence. Recurrent topics in Linghao Song's work include Advanced Memory and Neural Computing (23 papers), Advanced Neural Network Applications (14 papers) and Ferroelectric and Negative Capacitance Devices (13 papers). Linghao Song is often cited by papers focused on Advanced Memory and Neural Computing (23 papers), Advanced Neural Network Applications (14 papers) and Ferroelectric and Negative Capacitance Devices (13 papers). Linghao Song collaborates with scholars based in United States, China and Hong Kong. Linghao Song's co-authors include Yiran Chen, Hai Li, Xuehai Qian, Fan Chen, Youwei Zhuo, Yuan Xie, Tianqi Tang, Huanrui Yang, Wei Wen and Chenchen Liu and has published in prestigious journals such as IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, Computational Materials Science and Engineering.

In The Last Decade

Linghao Song

38 papers receiving 1.7k citations

Hit Papers

PipeLayer: A Pipelined ReRAM-Based Accelerator for Deep L... 2017 2026 2020 2023 2017 200 400 600
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. PipeLayer: A Pipelined ReRAM-Based Accelerator for Deep Learning
    2017 622 citations Linghao Song, Xuehai Qian et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Linghao Song United States 17 1.3k 583 569 327 303 40 1.7k
Ping Chi United States 12 1.3k 1.0× 366 0.6× 366 0.6× 357 1.1× 293 1.0× 23 1.6k
Zhezhi He United States 26 1.3k 1.0× 531 0.9× 857 1.5× 302 0.9× 235 0.8× 94 2.1k
Anirban Nag United States 6 1.4k 1.1× 414 0.7× 464 0.8× 261 0.8× 161 0.5× 6 1.7k
Priyanka Raina United States 14 1.3k 1.1× 460 0.8× 401 0.7× 400 1.2× 201 0.7× 64 1.8k
Liqiang He China 6 802 0.6× 664 1.1× 463 0.8× 246 0.8× 158 0.5× 20 1.3k
Bingjun Xiao United States 12 1.2k 0.9× 1.0k 1.7× 505 0.9× 497 1.5× 269 0.9× 18 1.9k
Ren-Shuo Liu Taiwan 23 2.0k 1.6× 251 0.4× 392 0.7× 415 1.3× 404 1.3× 73 2.4k
Hyoukjun Kwon United States 16 829 0.7× 703 1.2× 414 0.7× 576 1.8× 339 1.1× 38 1.6k
Swagath Venkataramani United States 25 1.8k 1.5× 590 1.0× 532 0.9× 784 2.4× 299 1.0× 66 2.3k
Dimin Niu United States 25 1.4k 1.1× 269 0.5× 323 0.6× 809 2.5× 755 2.5× 67 2.0k

Countries citing papers authored by Linghao Song

Since Specialization
Citations

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

Fields of papers citing papers by Linghao Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Linghao Song

This figure shows the co-authorship network connecting the top 25 collaborators of Linghao Song. A scholar is included among the top collaborators of Linghao Song 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 Linghao Song. Linghao Song 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.
2.
Li, Shiyu, Qilin Zheng, Linghao Song, et al.. (2024). NDSEARCH: Accelerating Graph-Traversal-Based Approximate Nearest Neighbor Search through Near Data Processing. 368–381. 7 indexed citations
3.
Song, Linghao, et al.. (2024). LevelST: Stream-based Accelerator for Sparse Triangular Solver. 67–77. 2 indexed citations
4.
Chi, Yuze, et al.. (2024). TAPA-CS: Enabling Scalable Accelerator Design on Distributed HBM-FPGAs. 966–980. 1 indexed citations
5.
Guo, Licheng, Christopher Lavin, Eddie Hung, et al.. (2023). RapidStream 2.0: Automated Parallel Implementation of Latency–Insensitive FPGA Designs Through Partial Reconfiguration. ACM Transactions on Reconfigurable Technology and Systems. 16(4). 1–30. 5 indexed citations
6.
7.
Chen, Fan, Linghao Song, Hai Li, & Yiran Chen. (2021). RAISE: A Resistive Accelerator for Subject-Independent EEG Signal Classification. 340–343. 1 indexed citations
8.
Dai, Pengcheng, Jianlei Yang, Junyu Luo, et al.. (2020). SparseTrain: Exploiting Dataflow Sparsity for Efficient Convolutional Neural Networks Training. 1–6. 16 indexed citations
9.
Song, Linghao, Fan Chen, Youwei Zhuo, et al.. (2020). AccPar: Tensor Partitioning for Heterogeneous Deep Learning Accelerators. 342–355. 40 indexed citations
10.
Chen, Fan, Linghao Song, Hai Li, & Yiran Chen. (2020). PARC: A Processing-in-CAM Architecture for Genomic Long Read Pairwise Alignment using ReRAM. 175–180. 17 indexed citations
11.
Song, Linghao, et al.. (2020). Parallelism in Deep Learning Accelerators. 645–650. 2 indexed citations
12.
Yang, Huanrui, et al.. (2019). DPATCH: An Adversarial Patch Attack on Object Detectors.. National Conference on Artificial Intelligence. 27 indexed citations
13.
Chen, Fan, et al.. (2019). How to Obtain and Run Light and Efficient Deep Learning Networks. 1–5. 1 indexed citations
14.
Bogdan, Paul, Fan Chen, Aryan Deshwal, et al.. (2019). Taming extreme heterogeneity via machine learning based design of autonomous manycore systems. 1–10. 3 indexed citations
15.
Song, Linghao, et al.. (2019). ZARA. 1–6. 23 indexed citations
16.
Chen, Fan, Linghao Song, & Yiran Chen. (2018). ReGAN: A pipelined ReRAM-based accelerator for generative adversarial networks. 178–183. 56 indexed citations
17.
Ji, Houxiang, et al.. (2018). ReCom: An efficient resistive accelerator for compressed deep neural networks. 237–240. 55 indexed citations
18.
Song, Linghao, et al.. (2018). Study of the effect of osmotic pressure on the water permeability of carbon-based two-dimensional materials. Computational Materials Science. 150. 9–14. 2 indexed citations
19.
Wang, Yandan, Wei Wen, Linghao Song, & Hai Li. (2017). Classification accuracy improvement for neuromorphic computing systems with one-level precision synapses. 776–781. 19 indexed citations
20.
Song, Linghao, et al.. (2016). NVSim-VX s. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 1–6. 9 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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