Bin Gu

520 citations
16 papers · 243 · 1 hit paper · h-index 5

Impact in

Papers in

Bin Gu

13 papers receiving 232 citations

Bin Gu's Hit Papers

Managing Artificial Intelligence 2021 · 199 citations
1990+1+3Years since publication50100150

Peers

Bin Gu
Comparison fields: 5 of 49
  • Health Informatics 11
  • Safety Research 52
  • Management Information Systems 34
  • Signal Processing 32
  • Artificial Intelligence 74
Replace Peyman Najafirad with:
Peyman Najafirad United States
Ding Ding Singapore
K. Valerie Carl Germany
Sofia Sherman Israel
Teemu Birkstedt Finland
Moritz von Zahn Germany
Riikka Koulu Finland
Federico Casolari Italy
Benjamin Sturm Germany
Bernhard Waltl Germany
Bin Gu relative to Peyman Najafirad United States Peyman Najafirad's profile →
Citations per field
00.5×5.1×
Peyman Najafirad · 1×
Citations per year

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-authors

The 25 scholars most cited alongside Bin Gu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bin Gu Line = papers co-authored together Bin Gu links everyone, so they are left out of the graph.

All Works

16 of 16 papers shown
#Work
1
Managing Artificial Intelligence
Hit paper breakdown →
2021199
2 20218
3 20248
4 20205
5 20215
6 20213
7 20183
8 20223
9 20232
10 19982
11 20232
12 20242
13 20201
14 20250
15 20250
16 20160

About Bin Gu

Bin Gu is a scholar working on Artificial Intelligence, Signal Processing, Management Information Systems, Information Systems and Computer Vision and Pattern Recognition, having authored 16 papers that have together received 243 indexed citations. Recurring topics across this work include Speech Recognition and Synthesis (10 papers), Speech and Audio Processing (10 papers), Music and Audio Processing (9 papers), Big Data and Business Intelligence (3 papers), Mineral Processing and Grinding (1 paper), Multimodal Machine Learning Applications (1 paper), Blockchain Technology Applications and Security (1 paper) and Topic Modeling (1 paper). The work is most often cited by research in Health Informatics (11 citations), Safety Research (52 citations), Management Information Systems (34 citations), Signal Processing (32 citations) and Artificial Intelligence (74 citations). Bin Gu has collaborated with scholars based in China, United States and Germany. Frequent co-authors include Nicholas Berente, Radhika Santhanam, Jan Recker, Wu Guo, Jie Zhang, Li-Rong Dai, Bin Zhang, Quan Liu, Yongchao Wang and Yingsheng Zhang. Their work appears in journals such as IEEE/ACM Transactions on Audio Speech and Language Processing, Journal of Management Analytics, IEEE Signal Processing Letters, MIS Quarterly and ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

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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