Cheng Ju
- Artificial Intelligence top 10%
- Statistics and Probability top 5%
- Molecular Biology
- Computer Vision and Pattern Recognition top 10%
- Economics and Econometrics top 10%
- Co-authors
- Mark van der LaanAurélien BibautMark J. van der LaanSebastian SchneeweißJessica M. FranklinRichard WyssSamuel LendleDavid Benkeser
- Topics
- Advanced Causal Inference Techniques (6 papers)Statistical Methods and Bayesian Inference (5 papers)Statistical Methods and Inference (5 papers)
- Partner nations
- ChinaUnited StatesTürkiye
In The Last Decade
Cheng Ju
35 papers receiving 686 citations
Peers
Comparison fields: 5 of 154
- Artificial Intelligence 153
- Statistics and Probability 126
- Molecular Biology 85
- Computer Vision and Pattern Recognition 83
- Economics and Econometrics 70
Countries citing papers authored by Cheng Ju
This map shows the geographic impact of Cheng Ju'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 Cheng Ju with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cheng Ju more than expected).
Fields of papers citing papers by Cheng Ju
This network shows the impact of papers produced by Cheng Ju. 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 Cheng Ju. The network helps show where Cheng Ju may publish in the future.
Co-authorship network of co-authors of Cheng Ju
This figure shows the co-authorship network connecting the top 25 collaborators of Cheng Ju. A scholar is included among the top collaborators of Cheng Ju 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 Cheng Ju. Cheng Ju is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 1 | |
| 4 | 27 | |
| 5 | 18 | |
| 6 | 2 | |
| 7 | 15 | |
| 8 | 8 | |
| 9 | 18 | |
| 10 | 18 | |
| 11 | 5 | |
| 12 | Non-convex Finite-Sum Optimization Via SCSG Methods | 23 |
| 13 | Research progress in pharmacological effects and clinical application of pine pollen. | 2 |
| 14 | Influences of climatic warming on potential distribution regions of Calymperes in China | 2 |
| 15 | Adverse drug reactions induced by montelukast | 1 |
| 16 | 1 | |
| 17 | 3 | |
| 18 | Clinical Observation of Moxibustion plus Auricular-seed-pressing Preventing 60 Cases with Gastrointestinal Reaction after Cisplatin treatment | 1 |
| 19 | Evaluation on TB control programme in Shandong province | 1 |
| 20 | The structure patterns and performance analysis of the double-telescopic props of hydraulic supports | 1 |
About Cheng Ju
Cheng Ju is a scholar working on Statistics and Probability, Developmental Neuroscience and Molecular Medicine, having authored 37 papers that have together received 704 indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (6 papers), Statistical Methods and Bayesian Inference (5 papers) and Statistical Methods and Inference (5 papers). The work is most often cited by research in Statistics and Probability (126 citations), Artificial Intelligence (153 citations) and Computer Vision and Pattern Recognition (83 citations). Cheng Ju has collaborated with scholars based in China, United States and Türkiye. Frequent co-authors include Mark van der Laan, Aurélien Bibaut, Mark J. van der Laan, Sebastian Schneeweiß, Jessica M. Franklin, Richard Wyss, Samuel Lendle, David Benkeser, Dan Zhang and Xiu‐Qi Bao. Their work appears in journals such as Biometrics, Carbohydrate Polymers and Optics Express.
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.