Ping‐Huan Kuo

3.0k total citations · 1 hit paper
97 papers, 2.1k citations indexed

About

Ping‐Huan Kuo is a scholar working on Artificial Intelligence, Mechanical Engineering and Computer Vision and Pattern Recognition. According to data from OpenAlex, Ping‐Huan Kuo has authored 97 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 26 papers in Artificial Intelligence, 26 papers in Mechanical Engineering and 23 papers in Computer Vision and Pattern Recognition. Recurrent topics in Ping‐Huan Kuo's work include Advanced machining processes and optimization (18 papers), Robotic Locomotion and Control (16 papers) and Robotic Path Planning Algorithms (11 papers). Ping‐Huan Kuo is often cited by papers focused on Advanced machining processes and optimization (18 papers), Robotic Locomotion and Control (16 papers) and Robotic Path Planning Algorithms (11 papers). Ping‐Huan Kuo collaborates with scholars based in Taiwan, China and Japan. Ping‐Huan Kuo's co-authors include Chiou‐Jye Huang, Tzuu‐Hseng S. Li, Her‐Terng Yau, Lifan Wu, Cheng‐Chi Wang, Guanying Chen, Yung‐Hsiang Chen, Yen‐Wen Chen, Jun Hu and Chih‐Yen Chen and has published in prestigious journals such as IEEE Access, Sensors and IEEE Transactions on Fuzzy Systems.

In The Last Decade

Ping‐Huan Kuo

85 papers receiving 2.0k citations

Hit Papers

A Deep CNN-LSTM Model for Particulate Matter (PM2.5) Fore... 2018 2026 2020 2023 2018 100 200 300 400 500
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.

  1. A Deep CNN-LSTM Model for Particulate Matter (PM2.5) Forecasting in Smart Cities
    2018 538 citations Chiou‐Jye Huang, Ping‐Huan Kuo profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Ping‐Huan Kuo Taiwan 20 783 532 470 321 252 97 2.1k
Hugo Valadares Siqueira Brazil 26 477 0.6× 509 1.0× 380 0.8× 242 0.8× 47 0.2× 102 1.6k
Hamdy K. Elminir Egypt 19 516 0.7× 716 1.3× 437 0.9× 337 1.0× 114 0.5× 51 2.2k
Abdelkader Dairi Algeria 19 269 0.3× 569 1.1× 207 0.4× 85 0.3× 95 0.4× 44 1.5k
Ning Jin China 20 830 1.1× 761 1.4× 133 0.3× 86 0.3× 364 1.4× 97 2.4k
Zheng O’Neill United States 37 1.4k 1.8× 390 0.7× 1.3k 2.7× 169 0.5× 128 0.5× 152 4.7k
Annamária R. Várkonyi-Kóczy Hungary 20 396 0.5× 492 0.9× 230 0.5× 49 0.2× 282 1.1× 156 1.9k
Junjing Yang Singapore 20 1.1k 1.4× 221 0.4× 809 1.7× 169 0.5× 133 0.5× 28 2.4k
Xiaodong Xu China 33 2.0k 2.6× 549 1.0× 510 1.1× 108 0.3× 318 1.3× 329 3.9k
Chao‐Tung Yang Taiwan 26 361 0.5× 362 0.7× 248 0.5× 154 0.5× 209 0.8× 318 2.8k
Neeraj Dhanraj Bokde India 23 608 0.8× 376 0.7× 225 0.5× 29 0.1× 289 1.1× 74 1.9k

Countries citing papers authored by Ping‐Huan Kuo

Since Specialization
Citations

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

Fields of papers citing papers by Ping‐Huan Kuo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Ping‐Huan Kuo. 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 Ping‐Huan Kuo. The network helps show where Ping‐Huan Kuo may publish in the future.

Co-authorship network of co-authors of Ping‐Huan Kuo

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

All Works

20 of 20 papers shown
1.
Yau, Her‐Terng, et al.. (2025). Data-Driven Tool Remaining Useful Life Prediction in Ceramic Grinding: A Multisensor Machine Learning Approach. IEEE Sensors Journal. 25(23). 43223–43234.
2.
Kuo, Ping‐Huan, et al.. (2024). Development of feline infectious peritonitis diagnosis system by using CatBoost algorithm. Computational Biology and Chemistry. 113. 108227–108227. 1 indexed citations
3.
Kuo, Ping‐Huan, et al.. (2024). A machine learning-based motion training approach applied to multilegged and bipedal robots. Control Engineering Practice. 147. 105913–105913. 2 indexed citations
4.
Kuo, Ping‐Huan, et al.. (2024). Milling wear prediction using an artificial neural network model. Engineering Applications of Artificial Intelligence. 135. 108686–108686. 7 indexed citations
5.
Wang, Cheng‐Chi, et al.. (2024). Voting model prediction of nonlinear behavior for double-circumferential-slot air bearing system. Chaos Solitons & Fractals. 183. 114908–114908.
6.
Yau, Her‐Terng, et al.. (2024). Carbon Emissions and Parameter Optimization for Machine Tool Processing. IEEE Sensors Journal. 24(17). 27225–27237. 2 indexed citations
7.
Kuo, Ping‐Huan, et al.. (2023). Intelligent proximal-policy-optimization-based decision-making system for humanoid robots. Advanced Engineering Informatics. 56. 102009–102009. 7 indexed citations
8.
Kuo, Ping‐Huan, et al.. (2023). Ensemble Model for Spindle Thermal Displacement Prediction of Machine Tools. Computer Modeling in Engineering & Sciences. 137(1). 319–343. 2 indexed citations
9.
Yau, Her‐Terng, et al.. (2023). Proximal policy optimization‐based controller for chaotic systems. International Journal of Robust and Nonlinear Control. 34(1). 586–601. 5 indexed citations
10.
Kuo, Ping‐Huan, et al.. (2023). Sequential sensor fusion-based W-DDPG gait controller of bipedal robots for adaptive slope walking. Advanced Engineering Informatics. 57. 102067–102067. 4 indexed citations
11.
Kuo, Ping‐Huan, et al.. (2023). Two-stage fuzzy object grasping controller for a humanoid robot with proximal policy optimization. Engineering Applications of Artificial Intelligence. 125. 106694–106694. 2 indexed citations
12.
Huang, Chiou‐Jye, et al.. (2021). An Ensemble Model based on Deep Learning and Data Preprocessing for Short-Term Electrical Load Forecasting. Sustainability. 13(4). 1694–1694. 32 indexed citations
13.
Li, Tzuu‐Hseng S., et al.. (2020). Fuzzy Double Deep Q-Network-Based Gait Pattern Controller for Humanoid Robots. IEEE Transactions on Fuzzy Systems. 30(1). 147–161. 15 indexed citations
14.
Li, Tzuu‐Hseng S., et al.. (2020). Breast Cancer–Detection System Using PCA, Multilayer Perceptron, Transfer Learning, and Support Vector Machine. IEEE Access. 8. 204309–204324. 54 indexed citations
15.
Li, Tzuu‐Hseng S., et al.. (2020). Sequential Sensor Fusion-Based Real-Time LSTM Gait Pattern Controller for Biped Robot. IEEE Sensors Journal. 21(2). 2241–2255. 15 indexed citations
16.
Li, Tzuu‐Hseng S., et al.. (2019). CNN and LSTM Based Facial Expression Analysis Model for a Humanoid Robot. IEEE Access. 7. 93998–94011. 61 indexed citations
17.
Li, Tzuu‐Hseng S., et al.. (2019). Intelligent Control Strategy for Robotic Arm by Using Adaptive Inertia Weight and Acceleration Coefficients Particle Swarm Optimization. IEEE Access. 7. 126929–126940. 12 indexed citations
18.
Li, Tzuu‐Hseng S., et al.. (2016). Reciprocal Learning for Robot Peers. IEEE Access. 5. 6198–6211. 2 indexed citations
19.
Li, Tzuu‐Hseng S., et al.. (2016). Robots That Think Fast and Slow: An Example of Throwing the Ball Into the Basket. IEEE Access. 4. 5052–5064. 4 indexed citations
20.
Kuo, Ping‐Huan, et al.. (1976). A study on pesticide residues in umbilical cord blood and maternal milk.. PubMed. 75(8). 463–70. 6 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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