Tingli Su

2.4k total citations · 1 hit paper
76 papers, 1.7k citations indexed

About

Tingli Su is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Control and Systems Engineering. According to data from OpenAlex, Tingli Su has authored 76 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 27 papers in Artificial Intelligence, 26 papers in Electrical and Electronic Engineering and 13 papers in Control and Systems Engineering. Recurrent topics in Tingli Su's work include Target Tracking and Data Fusion in Sensor Networks (15 papers), Energy Load and Power Forecasting (12 papers) and Indoor and Outdoor Localization Technologies (12 papers). Tingli Su is often cited by papers focused on Target Tracking and Data Fusion in Sensor Networks (15 papers), Energy Load and Power Forecasting (12 papers) and Indoor and Outdoor Localization Technologies (12 papers). Tingli Su collaborates with scholars based in China, United Kingdom and Taiwan. Tingli Su's co-authors include Jianlei Kong, Xuebo Jin, Yuting Bai, Xiaoyi Wang, Yangyang Zheng, Min Zuo, Xiaoyi Wang, Xuebo Jin, Prąsun Chakrabarti and Bin Yan and has published in prestigious journals such as IEEE Access, Sensors and International Journal of Environmental Research and Public Health.

In The Last Decade

Tingli Su

70 papers receiving 1.7k 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.

CropDeep: The Crop Vision Dataset for Deep-Learning-Based Classification and Detection in Precision Agriculture

2019 321 citations Jianlei Kong, Xuebo Jin et al. Sensors profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Tingli Su China	21	437	376	331	292	274	76	1.7k
Xuebo Jin China	25	526 1.2×	506 1.3×	336 1.0×	388 1.3×	297 1.1×	76	2.1k
Jianlei Kong China	26	500 1.1×	626 1.7×	325 1.0×	300 1.0×	320 1.2×	90	2.3k
Yuting Bai China	24	467 1.1×	224 0.6×	347 1.0×	313 1.1×	257 0.9×	73	1.6k
Xiaoyi Wang China	28	505 1.2×	165 0.4×	428 1.3×	339 1.2×	295 1.1×	231	2.5k
A.E. Ruano Portugal	28	741 1.7×	283 0.8×	1.1k 3.2×	645 2.2×	415 1.5×	156	3.1k
Pauline Ong Malaysia	21	529 1.2×	142 0.4×	229 0.7×	243 0.8×	52 0.2×	93	1.7k
José Boaventura‐Cunha Portugal	22	260 0.6×	561 1.5×	199 0.6×	444 1.5×	167 0.6×	108	1.8k
Panagiotis Radoglou‐Grammatikis Greece	18	519 1.2×	264 0.7×	283 0.9×	621 2.1×	116 0.4×	76	1.9k
Nitin Goyal India	30	365 0.8×	489 1.3×	681 2.1×	99 0.3×	56 0.2×	126	2.7k
Flavio Esposito United States	23	324 0.7×	534 1.4×	363 1.1×	57 0.2×	302 1.1×	142	2.3k

Countries citing papers authored by Tingli Su

Since Specialization

Citations

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

Fields of papers citing papers by Tingli Su

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tingli Su

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

Bai, Yuting, et al.. (2025). A Novel Adaptive State Estimation Model: Kalman Filter Coupled With Neural Networks. International Journal of Adaptive Control and Signal Processing. 39(5). 914–926. 2 indexed citations

Jin, Xuebo, et al.. (2025). A Deep-Learning Detector via Optimized YOLOv7-bw Architecture for Dense Small Remote-Sensing Targets in Harsh Food Supply Applications. 2(1). 38–58.

Ma, Huijun, et al.. (2025). Cross-modal feature fusion via mutual assistance: a novel network for enhanced object detection. The Visual Computer. 41(13). 10827–10840. 1 indexed citations

Jin, Xuebo, et al.. (2024). GPS Tracking Based on Stacked-Serial LSTM Network. 1(1). 50–62. 4 indexed citations

Zhang, Yulei, Yuting Bai, Xuebo Jin, Zhiyao Zhao, & Tingli Su. (2024). A novel broad learning system integrated with restricted Boltzmann machine and echo state network for time series forecasting. Engineering Applications of Artificial Intelligence. 133. 108315–108315. 4 indexed citations

Zhou, Chenguang, et al.. (2024). Inertial Pose Estimation Method Based on Multi-Genre Cascade Networks. 8746–8751.

Bai, Yuting, Wei Jia, Xuebo Jin, Tingli Su, & Jianlei Kong. (2023). Location estimation based on feature mode matching with deep network models. Frontiers in Neurorobotics. 17. 1181864–1181864. 1 indexed citations

Jin, Xuebo, et al.. (2023). Parameter-Free State Estimation Based on Kalman Filter with Attention Learning for GPS Tracking in Autonomous Driving System. Sensors. 23(20). 8650–8650. 5 indexed citations

Zhang, Yulei, et al.. (2023). Deep Fusion Prediction Method for Nonstationary Time Series Based on Feature Augmentation and Extraction. Applied Sciences. 13(8). 5088–5088. 3 indexed citations

10.

Jin, Xuebo, et al.. (2023). Deep Spatio-Temporal Graph Network with Self-Optimization for Air Quality Prediction. Entropy. 25(2). 247–247. 68 indexed citations

11.

Bai, Yuting, et al.. (2023). Nonstationary Time Series Prediction Based on Deep Echo State Network Tuned by Bayesian Optimization. Mathematics. 11(6). 1503–1503. 7 indexed citations

12.

Kong, Jianlei, et al.. (2023). BMAE-Net: A Data-Driven Weather Prediction Network for Smart Agriculture. Agronomy. 13(3). 625–625. 38 indexed citations

13.

Bai, Yuting, Bin Yan, Chenguang Zhou, Tingli Su, & Xuebo Jin. (2023). State of art on state estimation: Kalman filter driven by machine learning. Annual Reviews in Control. 56. 100909–100909. 66 indexed citations

14.

Bai, Yuting, et al.. (2022). A Novel Broad Echo State Network for Time Series Prediction: Cascade of Mapping Nodes and Optimization of Enhancement Layer. Applied Sciences. 12(13). 6396–6396. 3 indexed citations

15.

Jin, Xuebo, et al.. (2021). Modeling and Analysis of Data‐Driven Systems through Computational Neuroscience Wavelet‐Deep Optimized Model for Nonlinear Multicomponent Data Forecasting. Computational Intelligence and Neuroscience. 2021(1). 8810046–8810046. 5 indexed citations

16.

Bai, Yuting, Xiaoyi Wang, Xuebo Jin, et al.. (2020). Adaptive filtering for MEMS gyroscope with dynamic noise model. ISA Transactions. 101. 430–441. 38 indexed citations

17.

Jin, Xuebo, et al.. (2020). Deep Hybrid Model Based on EMD with Classification by Frequency Characteristics for Long-Term Air Quality Prediction. Mathematics. 8(2). 214–214. 77 indexed citations

18.

Bai, Yuting, Xiaoyi Wang, Qian Sun, et al.. (2019). Spatio-Temporal Prediction for the Monitoring-Blind Area of Industrial Atmosphere Based on the Fusion Network. International Journal of Environmental Research and Public Health. 16(20). 3788–3788. 15 indexed citations

19.

Longo, S., et al.. (2018). Optimal and Robust Scheduling for Networked Control Systems. 5 indexed citations

20.

Liu, Shengkai, et al.. (2018). Pedestrian indoor navigation using foot-mounted IMU with multi-sensor data fusion. International Journal of Modelling Identification and Control. 30(4). 261–261. 4 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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