Bin Gu

408 total citations · 1 hit paper
16 papers, 180 citations indexed

About

Bin Gu is a scholar working on Artificial Intelligence, Signal Processing and Management Information Systems. According to data from OpenAlex, Bin Gu has authored 16 papers receiving a total of 180 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Artificial Intelligence, 10 papers in Signal Processing and 3 papers in Management Information Systems. Recurrent topics in Bin Gu's work include Speech and Audio Processing (10 papers), Speech Recognition and Synthesis (10 papers) and Music and Audio Processing (9 papers). Bin Gu is often cited by papers focused on Speech and Audio Processing (10 papers), Speech Recognition and Synthesis (10 papers) and Music and Audio Processing (9 papers). Bin Gu collaborates with scholars based in China, United States and Hong Kong. Bin Gu's co-authors include Jan Recker, Radhika Santhanam, Nicholas Berente, Wu Guo, Jie Zhang, Ming Fan, Vijay Mookerjee, Jun Du, Quan Liu and Wenting Zhao and has published in prestigious journals such as MIS Quarterly, IEEE Signal Processing Letters and IEEE/ACM Transactions on Audio Speech and Language Processing.

In The Last Decade

Bin Gu

14 papers receiving 169 citations

Hit Papers

align trajectories

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.

Managing Artificial Intelligence

2021 138 citations Nicholas Berente, Bin Gu et al. MIS Quarterly profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bin Gu China	5	67	46	32	30	20	16	180
Peyman Najafirad United States	6	68 1.0×	14 0.3×	21 0.7×	10 0.3×	24 1.2×	20	245
Ding Ding Singapore	7	38 0.6×	15 0.3×	12 0.4×	5 0.2×	30 1.5×	17	221
Arif Nurwidyantoro Australia	10	88 1.3×	25 0.5×	17 0.5×	7 0.2×	106 5.3×	19	210
Francisco Andrade Portugal	7	74 1.1×	21 0.5×	9 0.3×	15 0.5×	53 2.6×	26	177
Johannes M. Lehner Austria	6	59 0.9×	11 0.2×	13 0.4×	8 0.3×	8 0.4×	17	226
Bernhard Waltl Germany	8	73 1.1×	18 0.4×	38 1.2×	5 0.2×	77 3.9×	11	159
Paulius Jurčys Japan	7	63 0.9×	34 0.7×	9 0.3×	4 0.1×	32 1.6×	25	170
Mika Viljanen Finland	5	46 0.7×	79 1.7×	37 1.2×	1 0.0×	29 1.4×	16	199
Kevin Bauer Germany	6	88 1.3×	58 1.3×	30 0.9×	1 0.0×	23 1.1×	18	215
Riikka Koulu Finland	7	38 0.6×	50 1.1×	36 1.1×	2 0.1×	65 3.3×	27	173

Countries citing papers authored by Bin Gu

Since Specialization

Citations

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

Fields of papers citing papers by Bin Gu

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bin Gu

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

All Works

Sort: Min cites: Since: Top N: Style:

16 of 16 papers shown

1.

Dong, Yihong, et al.. (2025). Rethinking Repetition Problems of LLMs in Code Generation. 965–985.

2.

Guo, Wu, et al.. (2025). A Study of Multi-Scale Feature Learning From Pre-Trained Models on Speaker Verification. 1–5.

3.

Zhang, Jie, et al.. (2024). Robust Spoof Speech Detection Based on Multi-Scale Feature Aggregation and Dynamic Convolution. 10156–10160. 6 indexed citations

4.

Guo, Wu, et al.. (2024). Contrastive Learning and Inter-Speaker Distribution Alignment Based Unsupervised Domain Adaptation for Robust Speaker Verification. 3794–3798. 1 indexed citations

5.

Gu, Bin, Wu Guo, & Jie Zhang. (2023). Memory Storable Network Based Feature Aggregation for Speaker Representation Learning. IEEE/ACM Transactions on Audio Speech and Language Processing. 31. 643–655. 2 indexed citations

6.

Gu, Bin, Jie Zhang, & Wu Guo. (2023). A Dynamic Convolution Framework for Session-Independent Speaker Embedding Learning. IEEE/ACM Transactions on Audio Speech and Language Processing. 31. 3647–3658. 2 indexed citations

7.

Guo, Wu, et al.. (2022). Multi-Level Contrastive Learning for Cross-Lingual Alignment. ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). 7947–7951. 3 indexed citations

8.

Berente, Nicholas, Bin Gu, Jan Recker, & Radhika Santhanam. (2021). Managing Artificial Intelligence. MIS Quarterly. 45(3). 1433–1450. 138 indexed citations breakdown →

9.

Gu, Bin & Wu Guo. (2021). Dynamic Convolution With Global-Local Information for Session-Invariant Speaker Representation Learning. IEEE Signal Processing Letters. 29. 404–408. 8 indexed citations

10.

Guo, Wu, et al.. (2021). Bidirectional Multiscale Feature Aggregation for Speaker Verification. 71–75. 5 indexed citations

11.

Chen, Yafeng, et al.. (2021). Improved Meta-Learning Training for Speaker Verification. 1049–1053. 3 indexed citations

12.

Guo, Wu, et al.. (2020). Adaptive Speaker Normalization for CTC-Based Speech Recognition. 1266–1270. 1 indexed citations

13.

Gu, Bin, Wu Guo, Li-Rong Dai, & Jun Du. (2020). An Improved Deep Neural Network for Modeling Speaker Characteristics at Different Temporal Scales. 6814–6818. 5 indexed citations

14.

Zhang, Yingsheng, Ming Fan, Bin Gu, et al.. (2018). Business Values/Implications of AI and Machine Learning. 2(3). 121–129. 3 indexed citations

15.

Gu, Bin, Wei Jiang, & Chee‐Wee Tan. (2016). Theme: Embracing the Internet of Things to Drive Data-Driven Decisions. Journal of Management Analytics. 3(2). 189–190. 1 indexed citations

16.

Gu, Bin, et al.. (1998). Examination of Classification Accuracy of Neural Network and Its Application to Image Analysis of Excavation Face.. Shigen-to-Sozai. 114(3). 155–162. 2 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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