Jun Wang
Impact in
- Economics and Econometrics top 0.5%
- Complex Systems and Time Series Analysis
- Market Dynamics and Volatility
-
- Stock Market Forecasting Methods
Papers in
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- Complex Systems and Time Series Analysis 106
- Market Dynamics and Volatility 31
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- Chaos control and synchronization 57
- Co-authors
- Hongli Niu (15 shared papers)Fang Wen (8 shared papers)Jie Wang (1 shared paper)Ronghui Wu (7 shared papers)Liyun Ma (7 shared papers)Aniruddha Patil (7 shared papers)Junhuan Zhang (4 shared papers)Yifan Zhang (4 shared papers)
- Journals
- Physica A Statistical Mechanics and its Applications (27 papers)Energy (8 papers)Nonlinear Dynamics (8 papers)International Journal of Modern Physics C (6 papers)Physics Letters A (6 papers)
- Partner nations
- ChinaUnited StatesCanada
In The Last Decade
Jun Wang
236 papers receiving 4.6k citations
Jun Wang's Hit Papers
Peers
Comparison fields: 5 of 181
- Economics and Econometrics 1.8k
- Management Science and Operations Research 848
- Statistical and Nonlinear Physics 699
- Finance 499
- Polymers and Plastics 536
Countries citing papers authored by Jun Wang
This map shows the geographic impact of Jun Wang'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 Jun Wang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jun Wang more than expected).
Fields of papers citing papers by Jun Wang
This network shows the impact of papers produced by Jun Wang. 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 Jun Wang. The network helps show where Jun Wang may publish in the future.
Co-authors
The 25 scholars most cited alongside Jun Wang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 258 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Wearable and flexible electrochemical sensors for sweat analysis: a review Hit paper breakdown → | 2023 | 477 |
| 2 | 2019 | 256 | |
| 3 | 2020 | 184 | |
| 4 | 2020 | 178 | |
| 5 | 2015 | 124 | |
| 6 | 2016 | 121 | |
| 7 | 2012 | 107 | |
| 8 | 2018 | 105 | |
| 9 | 2017 | 91 | |
| 10 | 2021 | 90 | |
| 11 | 2020 | 81 | |
| 12 | 2023 | 79 | |
| 13 | 2018 | 76 | |
| 14 | 2011 | 70 | |
| 15 | 2013 | 68 | |
| 16 | 2018 | 65 | |
| 17 | 2023 | 64 | |
| 18 | 2020 | 60 | |
| 19 | 2014 | 59 | |
| 20 | 2010 | 57 |
About Jun Wang
Jun Wang is a scholar working on Economics and Econometrics, Statistical and Nonlinear Physics, Finance, Electrical and Electronic Engineering and Management Science and Operations Research, having authored 258 papers that have together received 4.7k indexed citations. Recurring topics across this work include Complex Systems and Time Series Analysis (106 papers), Chaos control and synchronization (57 papers), Financial Risk and Volatility Modeling (34 papers), Market Dynamics and Volatility (31 papers), Stock Market Forecasting Methods (26 papers), Energy Load and Power Forecasting (17 papers), Advanced Sensor and Energy Harvesting Materials (15 papers) and Nonlinear Dynamics and Pattern Formation (14 papers). The work is most often cited by research in Economics and Econometrics (1.8k citations), Management Science and Operations Research (848 citations), Statistical and Nonlinear Physics (699 citations), Finance (499 citations) and Polymers and Plastics (536 citations). Jun Wang has collaborated with scholars based in China, United States and Canada. Frequent co-authors include Hongli Niu, Fang Wen, Jie Wang, Ronghui Wu, Liyun Ma, Aniruddha Patil, Junhuan Zhang, Yifan Zhang, Lili Huang and Shuihong Zhu. Their work appears in journals such as Physica A Statistical Mechanics and its Applications, Energy, Nonlinear Dynamics, International Journal of Modern Physics C and Physics Letters A.
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.