Qiong Dai

967 total citations
30 papers, 703 citations indexed

About

Qiong Dai is a scholar working on Artificial Intelligence, Analytical Chemistry and Computer Networks and Communications. According to data from OpenAlex, Qiong Dai has authored 30 papers receiving a total of 703 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 9 papers in Analytical Chemistry and 8 papers in Computer Networks and Communications. Recurrent topics in Qiong Dai's work include Spectroscopy and Chemometric Analyses (9 papers), Advanced Chemical Sensor Technologies (6 papers) and Network Packet Processing and Optimization (5 papers). Qiong Dai is often cited by papers focused on Spectroscopy and Chemometric Analyses (9 papers), Advanced Chemical Sensor Technologies (6 papers) and Network Packet Processing and Optimization (5 papers). Qiong Dai collaborates with scholars based in China, Ireland and United States. Qiong Dai's co-authors include Da‐Wen Sun, Jun‐Hu Cheng, Xin‐An Zeng, Hongbin Pu, Zhenjie Xiong, Zhiwei Zhu, Dan Liŭ, Wenhong Gao, Xin‐An Zeng and Zhong Han and has published in prestigious journals such as Food Chemistry, Trends in Food Science & Technology and Critical Reviews in Food Science and Nutrition.

In The Last Decade

Qiong Dai

29 papers receiving 686 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Qiong Dai China	11	409	273	234	112	96	30	703
Xinjie Yu China	14	664 1.6×	252 0.9×	97 0.4×	120 1.1×	152 1.6×	26	875
Xinhao Yang China	14	244 0.6×	110 0.4×	35 0.1×	94 0.8×	133 1.4×	41	624
Pierantonio Facco Italy	21	385 0.9×	174 0.6×	117 0.5×	218 1.9×	58 0.6×	70	1.1k
Sylvie Roussel France	10	439 1.1×	253 0.9×	57 0.2×	90 0.8×	148 1.5×	14	691
Himer Ávila-George Mexico	15	221 0.5×	100 0.4×	45 0.2×	46 0.4×	20 0.2×	60	657
Laijun Sun China	16	527 1.3×	172 0.6×	48 0.2×	66 0.6×	158 1.6×	68	885
Marion O’Farrell Norway	13	235 0.6×	159 0.6×	176 0.8×	60 0.5×	65 0.7×	40	463
José Emilio Guerrero-Ginel Spain	18	677 1.7×	266 1.0×	342 1.5×	130 1.2×	283 2.9×	43	989
Andrés Caro Spain	16	245 0.6×	139 0.5×	232 1.0×	128 1.1×	10 0.1×	45	611

Countries citing papers authored by Qiong Dai

Since Specialization

Citations

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

Fields of papers citing papers by Qiong Dai

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Qiong Dai

This figure shows the co-authorship network connecting the top 25 collaborators of Qiong Dai. A scholar is included among the top collaborators of Qiong 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 Qiong Dai. Qiong Dai 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

Zhao, Xusheng, Qiong Dai, Xu Bai, et al.. (2024). Reinforced GNNs for Multiple Instance Learning. IEEE Transactions on Neural Networks and Learning Systems. 36(4). 6693–6707.

Zhao, Xusheng, et al.. (2024). RDGCN: Reinforced Dependency Graph Convolutional Network for Aspect-based Sentiment Analysis. 976–984. 12 indexed citations

Zhang, Yujun, et al.. (2024). Coarse-to-fine label propagation with hybrid representation for deep semi-supervised bot detection. Wireless Networks. 31(2). 1321–1336. 1 indexed citations

Wu, Yan, Mingyue Wang, Ping Hou, et al.. (2024). Artificial intelligence assisted automatic screening of opportunistic osteoporosis in computed tomography images from different scanners. European Radiology. 35(4). 2287–2295. 7 indexed citations

Zhao, Xusheng, et al.. (2023). Multi-omics Sampling-based Graph Transformer for Synthetic Lethality Prediction. 785–792. 2 indexed citations

Zhao, Xusheng, Qiong Dai, Jia Wu, et al.. (2022). Multi-View Tensor Graph Neural Networks Through Reinforced Aggregation. IEEE Transactions on Knowledge and Data Engineering. 35(4). 4077–4091. 30 indexed citations

Zhi-gao, XU, Lili Zhao, Lei Yin, et al.. (2022). MRI-based machine learning model: A potential modality for predicting cognitive dysfunction in patients with type 2 diabetes mellitus. Frontiers in Bioengineering and Biotechnology. 10. 1082794–1082794. 8 indexed citations

Dai, Qiong, et al.. (2021). Cross-Network Community Sensing for Anchor Link Prediction. 1–8. 5 indexed citations

Yang, Jiajia, et al.. (2018). A High-Performance Round-Robin Regular Expression Matching Architecture Based on FPGA. 1–7. 6 indexed citations

10.

Wang, Changjian, et al.. (2018). Inspecting Influences on Likes and Comments of Photos in Instagram. 938–945. 2 indexed citations

11.

Yang, Jiajia, Lei Jiang, Qiu Tang, Qiong Dai, & Jianlong Tan. (2016). PiDFA: A practical multi-stride regular expression matching engine based On FPGA. 1–7. 10 indexed citations

12.

Dai, Qiong, Jun‐Hu Cheng, Da‐Wen Sun, Zhiwei Zhu, & Hongbin Pu. (2015). Prediction of total volatile basic nitrogen contents using wavelet features from visible/near-infrared hyperspectral images of prawn (Metapenaeus ensis). Food Chemistry. 197(Pt A). 257–265. 109 indexed citations

13.

Yan, Chenggang, et al.. (2015). Fast approximate matching of binary codes with distinctive bits. Frontiers of Computer Science. 9(5). 741–750. 5 indexed citations

14.

Xiong, Zhenjie, Da‐Wen Sun, Hongbin Pu, Wenhong Gao, & Qiong Dai. (2015). Applications of emerging imaging techniques for meat quality and safety detection and evaluation: A review. Critical Reviews in Food Science and Nutrition. 57(4). 755–768. 65 indexed citations

15.

Dai, Qiong, Jun‐Hu Cheng, Da‐Wen Sun, & Xin‐An Zeng. (2014). Advances in Feature Selection Methods for Hyperspectral Image Processing in Food Industry Applications: A Review. Critical Reviews in Food Science and Nutrition. 55(10). 1368–1382. 90 indexed citations

16.

Jiang, Lei, Qiong Dai, Qiu Tang, Jianlong Tan, & Binxing Fang. (2014). A fast regular expression matching engine for NIDS applying prediction scheme. 1–7. 10 indexed citations

17.

Dai, Qiong, Jun‐Hu Cheng, Da‐Wen Sun, et al.. (2014). Potential of visible/near-infrared hyperspectral imaging for rapid detection of freshness in unfrozen and frozen prawns. Journal of Food Engineering. 149. 97–104. 40 indexed citations

18.

Dai, Qiong, Jun‐Hu Cheng, Da‐Wen Sun, & Xin‐An Zeng. (2014). Potential of hyperspectral imaging for non-invasive determination of mechanical properties of prawn (Metapenaeus ensis). Journal of Food Engineering. 136. 64–72. 24 indexed citations

19.

Xiong, Zhenjie, Da‐Wen Sun, Qiong Dai, et al.. (2014). Application of Visible Hyperspectral Imaging for Prediction of Springiness of Fresh Chicken Meat. Food Analytical Methods. 8(2). 380–391. 57 indexed citations

20.

Dai, Qiong, Da‐Wen Sun, Zhenjie Xiong, Jun‐Hu Cheng, & Xin‐An Zeng. (2014). Recent Advances in Data Mining Techniques and Their Applications in Hyperspectral Image Processing for the Food Industry. Comprehensive Reviews in Food Science and Food Safety. 13(5). 891–905. 48 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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