Tian Gao
- Artificial Intelligence top 5%
- Management Science and Operations Research top 10%
- Computer Vision and Pattern Recognition top 10%
- Information Systems top 10%
- Computational Theory and Mathematics top 10%
- Co-authors
- Qiang JiDebarun BhattacharjyaDharmashankar SubramanianJunping DuMo YuKartik TalamadupulaPavan KapanipathiKshitij Fadnis
- Topics
- Bayesian Modeling and Causal Inference (15 papers)Data Quality and Management (9 papers)Topic Modeling (8 papers)
- Journals
- Computer Methods in Applied Mechanics and EngineeringIEEE Transactions on CyberneticsStructural and Multidisciplinary Optimization
- Partner nations
- United StatesChinaRussia
In The Last Decade
Tian Gao
33 papers receiving 325 citations
Peers
Comparison fields: 5 of 76
- Artificial Intelligence 264
- Management Science and Operations Research 74
- Computer Vision and Pattern Recognition 61
- Information Systems 52
- Computational Theory and Mathematics 50
Countries citing papers authored by Tian Gao
This map shows the geographic impact of Tian Gao'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 Tian Gao with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tian Gao more than expected).
Fields of papers citing papers by Tian Gao
This network shows the impact of papers produced by Tian Gao. 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 Tian Gao. The network helps show where Tian Gao may publish in the future.
Co-authorship network of co-authors of Tian Gao
This figure shows the co-authorship network connecting the top 25 collaborators of Tian Gao. A scholar is included among the top collaborators of Tian Gao 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 Tian Gao. Tian Gao is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 5 | |
| 3 | 3 | |
| 4 | 13 | |
| 5 | Causal Inference for Event Pairs in Multivariate Point Processes | 1 |
| 6 | 1 | |
| 7 | Hawkesian Graphical Event Models | 3 |
| 8 | 3 | |
| 9 | Generalized Linear Rule Models | 4 |
| 10 | 11 | |
| 11 | Identifying the Discourse Function of News Article Paragraphs | 15 |
| 12 | Parallel Bayesian Network Structure Learning | 4 |
| 13 | Proximal Graphical Event Models | 17 |
| 14 | Local-to-Global Bayesian Network Structure Learning. | 14 |
| 15 | Constrained local latent variable discovery | 2 |
| 16 | 26 | |
| 17 | 4 | |
| 18 | Local causal discovery of direct causes and effects | 24 |
| 19 | 6 | |
| 20 | 7 |
About Tian Gao
Tian Gao is a scholar working on Artificial Intelligence, Management Science and Operations Research and Signal Processing, having authored 37 papers that have together received 351 indexed citations. Recurring topics across this work include Bayesian Modeling and Causal Inference (15 papers), Data Quality and Management (9 papers) and Topic Modeling (8 papers). The work is most often cited by research in Artificial Intelligence (264 citations), Management Science and Operations Research (74 citations) and Computational Mathematics (3 citations). Tian Gao has collaborated with scholars based in United States, China and Russia. Frequent co-authors include Qiang Ji, Debarun Bhattacharjya, Dharmashankar Subramanian, Junping Du, Mo Yu, Kartik Talamadupula, Pavan Kapanipathi, Kshitij Fadnis, Murray Campbell and Karthikeyan Shanmugam. Their work appears in journals such as Computer Methods in Applied Mechanics and Engineering, IEEE Transactions on Cybernetics and Structural and Multidisciplinary Optimization.
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.