Jianfeng Du

1.6k total citations
56 papers, 1.1k citations indexed

About

Jianfeng Du is a scholar working on Artificial Intelligence, Information Systems and Inorganic Chemistry. According to data from OpenAlex, Jianfeng Du has authored 56 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Artificial Intelligence, 14 papers in Information Systems and 14 papers in Inorganic Chemistry. Recurrent topics in Jianfeng Du's work include Semantic Web and Ontologies (18 papers), Covalent Organic Framework Applications (14 papers) and Metal-Organic Frameworks: Synthesis and Applications (14 papers). Jianfeng Du is often cited by papers focused on Semantic Web and Ontologies (18 papers), Covalent Organic Framework Applications (14 papers) and Metal-Organic Frameworks: Synthesis and Applications (14 papers). Jianfeng Du collaborates with scholars based in China, United Kingdom and Australia. Jianfeng Du's co-authors include Zhiqiang Liang, Yuchuan Liu, Xiaowei Song, Guilin Qi, Yuanzheng Cui, Jeff Z. Pan, Shun Wang, Yue Yu, Hai Wan and Yi-Dong Shen and has published in prestigious journals such as ACS Applied Materials & Interfaces, Chemistry - A European Journal and RSC Advances.

In The Last Decade

Jianfeng Du

52 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jianfeng Du China 17 543 510 338 168 134 56 1.1k
Zhiling Zheng United States 14 742 1.4× 573 1.1× 88 0.3× 215 1.3× 25 0.2× 26 1.4k
Ying‐Hua Zhou China 22 595 1.1× 452 0.9× 38 0.1× 47 0.3× 63 0.5× 75 1.6k
Muhammad Ashraf Shaheen Pakistan 20 238 0.4× 127 0.2× 115 0.3× 32 0.2× 68 0.5× 78 1.1k
G. López Spain 32 485 0.9× 936 1.8× 63 0.2× 24 0.1× 65 0.5× 183 3.6k
Limin Han China 16 311 0.6× 126 0.2× 62 0.2× 135 0.8× 12 0.1× 125 1.1k
Reji Thomas India 20 610 1.1× 126 0.2× 80 0.2× 289 1.7× 188 1.4× 50 1.3k
Shuncheng Liu United States 27 837 1.5× 1.1k 2.1× 85 0.3× 15 0.1× 22 0.2× 78 1.9k
Kyung-min Kim South Korea 14 139 0.3× 161 0.3× 64 0.2× 262 1.6× 28 0.2× 51 662
Zifan Li China 19 573 1.1× 528 1.0× 420 1.2× 101 0.6× 154 1.1× 40 1.4k
Justin A. M. Lummiss Canada 19 486 0.9× 202 0.4× 57 0.2× 64 0.4× 23 0.2× 19 1.9k

Countries citing papers authored by Jianfeng Du

Since Specialization
Citations

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

Fields of papers citing papers by Jianfeng Du

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jianfeng Du

This figure shows the co-authorship network connecting the top 25 collaborators of Jianfeng Du. A scholar is included among the top collaborators of Jianfeng Du 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 Jianfeng Du. Jianfeng Du 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.
Wan, Hai, et al.. (2024). End-to-End Learning of LTLf Formulae by Faithful LTLf Encoding. Proceedings of the AAAI Conference on Artificial Intelligence. 38(8). 9071–9079. 1 indexed citations
2.
3.
4.
Wan, Hai, et al.. (2023). A Noise-Tolerant Differentiable Learning Approach for Single Occurrence Regular Expression with Interleaving. Proceedings of the AAAI Conference on Artificial Intelligence. 37(4). 4809–4817. 3 indexed citations
5.
Du, Jianfeng, et al.. (2022). Bridging LTLf Inference to GNN Inference for Learning LTLf Formulae. Proceedings of the AAAI Conference on Artificial Intelligence. 36(9). 9849–9857. 5 indexed citations
6.
Wan, Hai, et al.. (2022). Teaching LTLf Satisfiability Checking to Neural Networks. Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence. 3292–3298. 2 indexed citations
7.
Du, Jianfeng, Yu Ye, Yuchuan Liu, et al.. (2021). Boosting selective C2H2/CH4, C2H4/CH4 and CO2/CH4 adsorption performance via 1,2,3-triazole functionalized triazine-based porous organic polymers. Chinese Journal of Chemical Engineering. 42. 64–72. 14 indexed citations
8.
Wan, Hai, et al.. (2021). FL-MSRE: A Few-Shot Learning based Approach to Multimodal Social Relation Extraction. Proceedings of the AAAI Conference on Artificial Intelligence. 35(15). 13916–13923. 12 indexed citations
9.
Cui, Yuanzheng, Jianfeng Du, Yuchuan Liu, et al.. (2018). Design and synthesis of a multifunctional porous N-rich polymer containing s-triazine and Tröger's base for CO2 adsorption, catalysis and sensing. Polymer Chemistry. 9(19). 2643–2649. 63 indexed citations
10.
Du, Jianfeng, Yuchuan Liu, Rajamani Krishna, et al.. (2018). Enhancing Gas Sorption and Separation Performance via Bisbenzimidazole Functionalization of Highly Porous Covalent Triazine Frameworks. ACS Applied Materials & Interfaces. 10(31). 26678–26686. 56 indexed citations
11.
Du, Jianfeng, et al.. (2017). Practical TBox Abduction Based on Justification Patterns. Proceedings of the AAAI Conference on Artificial Intelligence. 31(1). 2 indexed citations
12.
Yan, Siyu, Yujia Sun, Xiaohan Yang, et al.. (2017). Enhancement of visible-light-driven CO2 reduction performance using an amine-functionalized zirconium metal–organic framework. Dalton Transactions. 47(3). 909–915. 79 indexed citations
13.
Du, Jianfeng, Kewen Wang, & Yi-Dong Shen. (2015). Towards Tractable and Practical ABox Abduction over Inconsistent Description Logic Ontologies. Proceedings of the AAAI Conference on Artificial Intelligence. 29(1). 10 indexed citations
14.
Du, Jianfeng, Kewen Wang, & Yi-Dong Shen. (2014). A Tractable Approach to ABox Abduction over Description Logic Ontologies. Proceedings of the AAAI Conference on Artificial Intelligence. 28(1). 12 indexed citations
15.
Du, Jianfeng, et al.. (2014). A Practical Fine-grained Approach to Resolving Incoherent OWL 2 DL Terminologies. 919–928. 11 indexed citations
16.
Qi, Guilin, Qiu Ji, Jeff Z. Pan, & Jianfeng Du. (2011). Extending description logics with uncertainty reasoning in possibilistic logic. International Journal of Intelligent Systems. 26(4). 353–381. 28 indexed citations
17.
Du, Jianfeng, Guilin Qi, Yi-Dong Shen, & Jeff Z. Pan. (2011). Towards Practical ABox Abduction in Large OWL DL Ontologies. Proceedings of the AAAI Conference on Artificial Intelligence. 25(1). 1160–1165. 12 indexed citations
18.
Du, Jianfeng, Guilin Qi, & Jeff Z. Pan. (2010). Finding data tractable description logics for computing a minimum cost diagnosis based on ABox decomposition. Tsinghua Science & Technology. 15(6). 623–632. 1 indexed citations
19.
Qi, Guilin & Jianfeng Du. (2009). Model-based revision operators for terminologies in description logics. International Joint Conference on Artificial Intelligence. 891–897. 42 indexed citations
20.
Du, Jianfeng & Yi-Dong Shen. (2007). Partitioning ABoxes Based on Converting DL to Plain Datalog.. Description Logics. 3 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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