Xiaolong Ma

1.6k total citations
33 papers, 696 citations indexed

About

Xiaolong Ma is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence and Electrical and Electronic Engineering. According to data from OpenAlex, Xiaolong Ma has authored 33 papers receiving a total of 696 indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Computer Vision and Pattern Recognition, 19 papers in Artificial Intelligence and 11 papers in Electrical and Electronic Engineering. Recurrent topics in Xiaolong Ma's work include Advanced Neural Network Applications (23 papers), Advanced Memory and Neural Computing (7 papers) and Domain Adaptation and Few-Shot Learning (7 papers). Xiaolong Ma is often cited by papers focused on Advanced Neural Network Applications (23 papers), Advanced Memory and Neural Computing (7 papers) and Domain Adaptation and Few-Shot Learning (7 papers). Xiaolong Ma collaborates with scholars based in United States, China and Mexico. Xiaolong Ma's co-authors include Yanzhi Wang, Jian Tang, Xue Lin, Ning Liu, Cecilia Metra, Kaisheng Ma, Fabrizio Lombardi, Zhiyuan Xu, Jieping Ye and Jing Huang and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Communications of the ACM and IEEE Transactions on Geoscience and Remote Sensing.

In The Last Decade

Xiaolong Ma

31 papers receiving 681 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Xiaolong Ma United States	15	414	322	225	73	53	33	696
Hongxiang Fan United Kingdom	16	284 0.7×	228 0.7×	211 0.9×	27 0.4×	35 0.7×	43	541
Juhyoung Lee South Korea	17	378 0.9×	188 0.6×	444 2.0×	18 0.2×	65 1.2×	44	741
Ming‐Hwa Sheu Taiwan	17	319 0.8×	183 0.6×	571 2.5×	149 2.0×	73 1.4×	126	1.0k
M. B. Srinivas India	15	127 0.3×	171 0.5×	318 1.4×	123 1.7×	85 1.6×	87	685
Liangzhen Lai United States	14	415 1.0×	316 1.0×	530 2.4×	18 0.2×	94 1.8×	31	977
Tong Geng United States	18	368 0.9×	398 1.2×	339 1.5×	51 0.7×	213 4.0×	70	951
Bertrand Zavidovique France	11	483 1.2×	78 0.2×	184 0.8×	27 0.4×	60 1.1×	114	752
Suyog Gupta United States	8	456 1.1×	426 1.3×	270 1.2×	42 0.6×	106 2.0×	8	835
Mukul Sutaone India	10	163 0.4×	124 0.4×	124 0.6×	31 0.4×	42 0.8×	66	487
Roberto Muscedere Canada	13	115 0.3×	194 0.6×	290 1.3×	152 2.1×	40 0.8×	57	590

Countries citing papers authored by Xiaolong Ma

Since Specialization

Citations

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

Fields of papers citing papers by Xiaolong Ma

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaolong Ma

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

All Works

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20 of 20 papers shown

Ma, Xiaolong, et al.. (2025). Kinematic modeling and stability analysis for a wind turbine blade inspection robot. Journal of Zhejiang University. Science A. 26(2). 121–137.

Li, Gen, et al.. (2025). Adversarial Robust ViT-Based Automatic Modulation Recognition in Practical Deep Learning-Based Wireless Systems. 3672–3690.

Afghah, Fatemeh, et al.. (2024). FlameFinder: Illuminating Obscured Fire Through Smoke With Attentive Deep Metric Learning. IEEE Transactions on Geoscience and Remote Sensing. 62. 1–12. 2 indexed citations

Yuan, Geng, Alec Lu, Mengshu Sun, et al.. (2023). ESRU: Extremely Low-Bit and Hardware-Efficient Stochastic Rounding Unit Design for Low-Bit DNN Training. 1–6. 3 indexed citations

Sun, Mengshu, Zhengang Li, Alec Lu, et al.. (2022). FILM-QNN: Efficient FPGA Acceleration of Deep Neural Networks with Intra-Layer, Mixed-Precision Quantization. 134–145. 48 indexed citations

Xue, Qi, Geng Yuan, Sheng Li, et al.. (2022). Optimizing Data Layout for Training Deep Neural Networks. 548–554. 1 indexed citations

Zhang, Chunxia, Yongqin Zhang, Xiaofeng Wang, et al.. (2022). CAN: Context-assisted full Attention Network for brain tissue segmentation. Medical Image Analysis. 85. 102710–102710. 16 indexed citations

Ma, Xiaolong, Geng Yuan, Zhengang Li, et al.. (2022). BLCR: Towards Real-time DNN Execution with Block-based Reweighted Pruning. 1–8. 5 indexed citations

Ma, Xiaolong, Sheng Lin, Shaokai Ye, et al.. (2021). Non-Structured DNN Weight Pruning—Is It Beneficial in Any Platform?. IEEE Transactions on Neural Networks and Learning Systems. 33(9). 4930–4944. 55 indexed citations

10.

Guan, Hui, Shaoshan Liu, Xiaolong Ma, et al.. (2021). CoCoPIE. Communications of the ACM. 64(6). 62–68. 14 indexed citations

11.

Zhang, Tianyun, Xiaolong Ma, Zheng Zhan, et al.. (2021). A Unified DNN Weight Pruning Framework Using Reweighted Optimization Methods. 493–498. 14 indexed citations

12.

Yuan, Geng, Wei Niu, Xiaolong Ma, et al.. (2021). Towards Fast and Accurate Multi-Person Pose Estimation on Mobile Devices. 5012–5015. 2 indexed citations

13.

Zhan, Zheng, Yifan Gong, Zhengang Li, et al.. (2020). A Privacy-Preserving DNN Pruning and Mobile Acceleration Framework.. arXiv (Cornell University). 2 indexed citations

14.

Ma, Xiaolong, et al.. (2020). Accelerating Sparse CNN Inference on GPUs with Performance-Aware Weight Pruning. 267–278. 14 indexed citations

15.

Gong, Yifan, Zheng Zhan, Wei Niu, et al.. (2020). A Privacy-Preserving-Oriented DNN Pruning and Mobile Acceleration Framework. 119–124. 13 indexed citations

16.

Ma, Xiaolong, Wei Niu, Xue Lin, et al.. (2020). PCONV: The Missing but Desirable Sparsity in DNN Weight Pruning for Real-Time Execution on Mobile Devices. Proceedings of the AAAI Conference on Artificial Intelligence. 34(4). 5117–5124. 110 indexed citations

17.

Ma, Xiaolong, et al.. (2019). ResNet Can Be Pruned 60×: Introducing Network Purification and Unused Path Removal (P-RM) after Weight Pruning. 1–2. 24 indexed citations

18.

Wang, Yanzhi, Shaokai Ye, Zhezhi He, et al.. (2019). Non-structured DNN Weight Pruning Considered Harmful. 5 indexed citations

19.

Li, Hongjia, Ning Liu, Xiaolong Ma, et al.. (2019). ADMM-based Weight Pruning for Real-Time Deep Learning Acceleration on Mobile Devices. 501–506. 17 indexed citations

20.

Ma, Xiaolong, Jing Huang, Cecilia Metra, & Fabrizio Lombardi. (2008). Reversible Gates and Testability of One Dimensional Arrays of Molecular QCA. Journal of Electronic Testing. 24(1-3). 297–311. 80 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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