Junchuan Shi

969 total citations · 2 hit papers
8 papers, 722 citations indexed

About

Junchuan Shi is a scholar working on Automotive Engineering, Mechanical Engineering and Control and Systems Engineering. According to data from OpenAlex, Junchuan Shi has authored 8 papers receiving a total of 722 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Automotive Engineering, 5 papers in Mechanical Engineering and 2 papers in Control and Systems Engineering. Recurrent topics in Junchuan Shi's work include Advanced Battery Technologies Research (3 papers), Additive Manufacturing Materials and Processes (2 papers) and Gear and Bearing Dynamics Analysis (2 papers). Junchuan Shi is often cited by papers focused on Advanced Battery Technologies Research (3 papers), Additive Manufacturing Materials and Processes (2 papers) and Gear and Bearing Dynamics Analysis (2 papers). Junchuan Shi collaborates with scholars based in United States, Sweden and Australia. Junchuan Shi's co-authors include Dazhong Wu, Zhixiong Li, Ziyang Zhang, Kai Goebel, Zhongxiao Peng, Dikang Peng, Alexis V. Rivera, Ali P. Gordon, Jihua Gou and Ziyang Zhang and has published in prestigious journals such as Mechanical Systems and Signal Processing, Robotics and Computer-Integrated Manufacturing and Polymer Composites.

In The Last Decade

Junchuan Shi

8 papers receiving 693 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.

Prediction of surface roughness in extrusion-based additive manufacturing with machine learning

2019 316 citations Zhixiong Li, Ziyang Zhang et al. Robotics and Computer-Integrated Manufacturing profile →
Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks

2021 206 citations Junchuan Shi, Dikang Peng et al. Mechanical Systems and Signal Processing profile →

Peers

Countries citing papers authored by Junchuan Shi

Since Specialization

Citations

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

Fields of papers citing papers by Junchuan Shi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Junchuan Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Junchuan Shi. A scholar is included among the top collaborators of Junchuan Shi 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 Junchuan Shi. Junchuan Shi 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:

8 of 8 papers shown

#	Work	Indexed citations
1	Remaining Flying Time Prediction of Unmanned Aerial Vehicles Under Different Load Conditions 2023 ·Journal of Aerospace Information Systems ·Junchuan Shi, (unknown), Dazhong Wu	1
2	Data-Driven Online Prediction of Discharge Capacity and End-of-Discharge of Lithium-Ion Batteries 2023 ·Journal of Computing and Information Science in Engineering ·Junchuan Shi, Yupeng Wei, Dazhong Wu	1
3	Battery health management using physics-informed machine learning: Online degradation modeling and remaining useful life prediction 2022 ·Mechanical Systems and Signal Processing ·Junchuan Shi, Alexis V. Rivera, Dazhong Wu	94
4	Planetary gearbox fault diagnosis using bidirectional-convolutional LSTM networks breakdown → 2021 ·Mechanical Systems and Signal Processing ·Junchuan Shi, Dikang Peng, Zhongxiao Peng, (unknown), Kai Goebel, Dazhong Wu	206
5	Remaining Useful Life Prediction of Bearings Using Ensemble Learning: The Impact of Diversity in Base Learners and Features 2020 ·Journal of Computing and Information Science in Engineering ·Junchuan Shi, (unknown), Kai Goebel, Dazhong Wu	47
6	Predicting Flexural Strength of Additively Manufactured Continuous Carbon Fiber-Reinforced Polymer Composites Using Machine Learning 2020 ·Journal of Computing and Information Science in Engineering ·Ziyang Zhang, Junchuan Shi, (unknown), (unknown), Ali P. Gordon, Jihua Gou, Dazhong Wu	37
7	Prediction of surface roughness in extrusion-based additive manufacturing with machine learning breakdown → 2019 ·Robotics and Computer-Integrated Manufacturing ·Zhixiong Li, Ziyang Zhang, Junchuan Shi, Dazhong Wu	316
8	Characteristics of paper mill sludge‐wood fiber‐high‐density polyethylene composites 2012 ·Polymer Composites ·(unknown), (unknown), (unknown), Junchuan Shi	20

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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