Ruobin Gao

1.8k total citations · 2 hit papers
55 papers, 1.2k citations indexed

About

Ruobin Gao is a scholar working on Artificial Intelligence, Management Science and Operations Research and Environmental Engineering. According to data from OpenAlex, Ruobin Gao has authored 55 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 16 papers in Management Science and Operations Research and 13 papers in Environmental Engineering. Recurrent topics in Ruobin Gao's work include Energy Load and Power Forecasting (11 papers), Stock Market Forecasting Methods (10 papers) and Forecasting Techniques and Applications (9 papers). Ruobin Gao is often cited by papers focused on Energy Load and Power Forecasting (11 papers), Stock Market Forecasting Methods (10 papers) and Forecasting Techniques and Applications (9 papers). Ruobin Gao collaborates with scholars based in Singapore, Qatar and China. Ruobin Gao's co-authors include Ponnuthurai Nagaratnam Suganthan, Kum Fai Yuen, Liang Du, Ruilin Li, David Z.W. Wang, Okan Duru, Minghui Hu, M. Tanveer, M. A. Ganaie and Qin Zhou and has published in prestigious journals such as Applied Energy, Expert Systems with Applications and Sensors.

In The Last Decade

Ruobin Gao

52 papers receiving 1.2k 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.

Bayesian optimization based dynamic ensemble for time series forecasting

2022 155 citations Liang Du, Ruobin Gao et al. profile →
Random vector functional link network: Recent developments, applications, and future directions

2023 103 citations Ruobin Gao, M. Tanveer et al. Applied Soft Computing profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Ruobin Gao Singapore	21	374	341	260	204	141	55	1.2k
Neeraj Dhanraj Bokde India	23	376 1.0×	608 1.8×	148 0.6×	225 1.1×	117 0.8×	74	1.9k
Alaa Sagheer Egypt	13	318 0.9×	256 0.8×	224 0.9×	120 0.6×	159 1.1×	33	1.2k
Martin Längkvist Sweden	9	379 1.0×	203 0.6×	136 0.5×	140 0.7×	83 0.6×	26	1.5k
Alaa Sheta United States	24	665 1.8×	307 0.9×	151 0.6×	155 0.8×	47 0.3×	140	2.0k
Greg Van Houdt Belgium	3	289 0.8×	229 0.7×	92 0.4×	128 0.6×	54 0.4×	4	1.2k
Eiji Mizutani Taiwan	10	727 1.9×	280 0.8×	100 0.4×	153 0.8×	69 0.5×	48	1.6k
Shun Chen China	9	452 1.2×	203 0.6×	91 0.3×	77 0.4×	43 0.3×	14	1.2k
Maryam Imani Iran	22	285 0.8×	409 1.2×	109 0.4×	126 0.6×	33 0.2×	147	1.9k
Marcello Restelli Italy	22	705 1.9×	219 0.6×	278 1.1×	79 0.4×	221 1.6×	143	1.6k
Haikun Wei China	22	682 1.8×	807 2.4×	143 0.6×	127 0.6×	26 0.2×	165	1.9k

Countries citing papers authored by Ruobin Gao

Since Specialization

Citations

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

Fields of papers citing papers by Ruobin Gao

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ruobin Gao

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

Gao, Ruobin, et al.. (2025). Underwater Acoustic Signal Denoising Algorithms: A Survey of the State of the Art. IEEE Transactions on Instrumentation and Measurement. 74. 1–18. 3 indexed citations

Gao, Ruobin, et al.. (2025). Stacked Ensemble Deep Random Vector Functional Link Network With Residual Learning for Medium-Scale Time-Series Forecasting. IEEE Transactions on Neural Networks and Learning Systems. 36(6). 10833–10843. 2 indexed citations

Gao, Ruobin, et al.. (2025). Wave energy forecasting: A state-of-the-art survey and a comprehensive evaluation. Applied Soft Computing. 170. 112652–112652. 1 indexed citations

Wang, Changdong, Huamin Jie, Jingli Yang, et al.. (2025). A Virtual Domain-Driven Semi-Supervised Hyperbolic Metric Network With Domain-Class Adversarial Decoupling for Aircraft Engine Intershaft Bearings Fault diagnosis. IEEE Transactions on Systems Man and Cybernetics Systems. 55(11). 7950–7963. 1 indexed citations

Liang, Maohan, et al.. (2025). Spatial–Frequency Fusion Network With Learnable Fractional Fourier Transform for Remote Sensing Imaging Enhancement. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 18. 17610–17621.

Li, Ruilin, Minghui Hu, Ruobin Gao, et al.. (2024). TFormer: A time–frequency Transformer with batch normalization for driver fatigue recognition. Advanced Engineering Informatics. 62. 102575–102575. 25 indexed citations

Liang, Maohan, et al.. (2024). Estimation of vessel link-level travel time distribution: A directed network-driven approach. Ocean Engineering. 313. 119371–119371. 2 indexed citations

Song, Wenwen, et al.. (2024). Two-Stage Combined Model for Short-Term Electricity Forecasting in Ports. Information. 15(11). 715–715. 1 indexed citations

Li, Huanhuan, Hang Jiao, Kum Fai Yuen, et al.. (2024). Bi-directional information fusion-driven deep network for ship trajectory prediction in intelligent transportation systems. Transportation Research Part E Logistics and Transportation Review. 192. 103770–103770. 17 indexed citations

10.

Gao, Ruobin, et al.. (2024). Wind Speed Forecasting Using an Ensemble Deep Random Vector Functional Link Neural Network Based on Parsimonious Channel Mixing. 1–8. 1 indexed citations

11.

Liang, Maohan, et al.. (2023). Unsupervised maritime anomaly detection for intelligent situational awareness using AIS data. Knowledge-Based Systems. 284. 111313–111313. 44 indexed citations

12.

Gao, Ruobin, et al.. (2023). A new perspective on air quality index time series forecasting: A ternary interval decomposition ensemble learning paradigm. Technological Forecasting and Social Change. 191. 122504–122504. 25 indexed citations

13.

Snåšel, Václav, Martin Štěpnička, Varun Ojha, et al.. (2023). Large-scale data classification based on the integrated fusion of fuzzy learning and graph neural network. Information Fusion. 102. 102067–102067. 8 indexed citations

14.

Li, Ruilin, et al.. (2023). An enhanced ensemble deep random vector functional link network for driver fatigue recognition. Engineering Applications of Artificial Intelligence. 123. 106237–106237. 21 indexed citations

15.

Gao, Ruobin, et al.. (2023). Learning-Based Motion-Intention Prediction for End-Point Control of Upper-Limb-Assistive Robots. Sensors. 23(6). 2998–2998. 12 indexed citations

16.

Gao, Ruobin, et al.. (2023). Online ensemble deep random vector functional link for the assistive robots. Qatar University QSpace (Qatar University). 30. 1–8. 1 indexed citations

17.

Gao, Ruobin, Ruilin Li, Minghui Hu, Ponnuthurai Nagaratnam Suganthan, & Kum Fai Yuen. (2023). Online dynamic ensemble deep random vector functional link neural network for forecasting. Neural Networks. 166. 51–69. 34 indexed citations

18.

Hu, Minghui, Ruobin Gao, & Ponnuthurai Nagaratnam Suganthan. (2023). Self-Distillation for Randomized Neural Networks. IEEE Transactions on Neural Networks and Learning Systems. 35(11). 16119–16128. 3 indexed citations

19.

Li, Ruilin, Jian Cui, Ruobin Gao, et al.. (2022). Situation Awareness Recognition Using EEG and Eye-Tracking data: a pilot study. Fraunhofer-Publica (Fraunhofer-Gesellschaft). 209–212. 2 indexed citations

20.

Gao, Ruobin, Jiahui Liu, Liang Du, & Kum Fai Yuen. (2021). Shipping market forecasting by forecast combination mechanism. Maritime Policy & Management. 49(8). 1059–1074. 10 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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