Jiachen Mao

627 total citations
13 papers, 373 citations indexed

About

Jiachen Mao is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Jiachen Mao has authored 13 papers receiving a total of 373 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Computer Vision and Pattern Recognition, 6 papers in Artificial Intelligence and 3 papers in Electrical and Electronic Engineering. Recurrent topics in Jiachen Mao's work include Advanced Neural Network Applications (9 papers), Anomaly Detection Techniques and Applications (3 papers) and IoT and Edge/Fog Computing (2 papers). Jiachen Mao is often cited by papers focused on Advanced Neural Network Applications (9 papers), Anomaly Detection Techniques and Applications (3 papers) and IoT and Edge/Fog Computing (2 papers). Jiachen Mao collaborates with scholars based in United States and China. Jiachen Mao's co-authors include Yiran Chen, Kent W. Nixon, Xiang Chen, Christopher D. Krieger, Hai Li, Wei Wen, Chunpeng Wu, Linghao Song, Ang Li and Hai Li and has published in prestigious journals such as ACM Transactions on Embedded Computing Systems, ACM Transactions on Cyber-Physical Systems and Asia and South Pacific Design Automation Conference.

In The Last Decade

Jiachen Mao

13 papers receiving 368 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jiachen Mao United States	8	229	192	141	133	25	13	373
Christopher D. Krieger United States	7	137 0.6×	165 0.9×	104 0.7×	91 0.7×	51 2.0×	18	295
Jiashen Cao United States	9	173 0.8×	163 0.8×	94 0.7×	127 1.0×	56 2.2×	18	357
Kamyar Mirzazad Barijough United States	3	181 0.8×	217 1.1×	105 0.7×	114 0.9×	15 0.6×	6	348
Guy Boudoukh Israel	3	154 0.7×	55 0.3×	161 1.1×	87 0.7×	78 3.1×	3	296
Weinan Song United States	4	206 0.9×	49 0.3×	188 1.3×	131 1.0×	62 2.5×	8	354
Shuochao Yao United States	11	155 0.7×	90 0.5×	64 0.5×	110 0.8×	18 0.7×	19	312
Loc N. Huynh Singapore	4	209 0.9×	107 0.6×	70 0.5×	80 0.6×	27 1.1×	5	297
Alei Liang China	10	84 0.4×	159 0.8×	76 0.5×	74 0.6×	49 2.0×	40	314
Jiazhen Lin China	6	191 0.8×	25 0.1×	56 0.4×	179 1.3×	11 0.4×	14	317

Countries citing papers authored by Jiachen Mao

Since Specialization

Citations

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

Fields of papers citing papers by Jiachen Mao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiachen Mao

This figure shows the co-authorship network connecting the top 25 collaborators of Jiachen Mao. A scholar is included among the top collaborators of Jiachen Mao 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 Jiachen Mao. Jiachen Mao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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13 of 13 papers shown

1.

Mao, Jiachen, Qing Yang, Ang Li, et al.. (2022). Toward Efficient and Adaptive Design of Video Detection System with Deep Neural Networks. ACM Transactions on Embedded Computing Systems. 21(3). 1–21. 1 indexed citations

2.

Mao, Jiachen, Huanrui Yang, Ang Li, Hai Li, & Yiran Chen. (2021). TPrune. ACM Transactions on Cyber-Physical Systems. 5(3). 1–22. 28 indexed citations

3.

Yang, Qing, et al.. (2019). DASNet: Dynamic Activation Sparsity for Neural Network Efficiency Improvement. 1401–1405. 9 indexed citations

4.

Mao, Jiachen, Qing Yang, Ang Li, Hai Li, & Yiran Chen. (2019). MobiEye. 1–6. 7 indexed citations

5.

Mao, Jiachen, et al.. (2019). NeuralHMC. 394–399. 10 indexed citations

6.

Li, Bing, Wei Wen, Jiachen Mao, et al.. (2018). Running sparse and low-precision neural network: when algorithm meets hardware. Asia and South Pacific Design Automation Conference. 534–539. 8 indexed citations

7.

Li, Bing, et al.. (2018). Running sparse and low-precision neural network: When algorithm meets hardware. 534–539. 13 indexed citations

8.

Nixon, Kent W., et al.. (2018). SPN dash. 1–6. 2 indexed citations

9.

Mao, Jiachen, Xiang Chen, Kent W. Nixon, Christopher D. Krieger, & Yiran Chen. (2017). MoDNN: Local distributed mobile computing system for Deep Neural Network. 1396–1401. 211 indexed citations

10.

Mao, Jiachen, Wei Wen, Chunpeng Wu, et al.. (2017). MeDNN: A distributed mobile system with enhanced partition and deployment for large-scale DNNs. 751–756. 63 indexed citations

11.

Mao, Jiachen, Zhuwei Qin, Zirui Xu, et al.. (2017). AdaLearner: An adaptive distributed mobile learning system for neural networks. 291–296. 7 indexed citations

12.

Chen, Xiang, Jiachen Mao, Kent W. Nixon, & Yiran Chen. (2016). MORPh. 7–11. 1 indexed citations

13.

Chen, Xiang, et al.. (2016). MORPh. 1–6. 13 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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