Peng Jiang

4.1k total citations · 1 hit paper
58 papers, 2.0k citations indexed

About

Peng Jiang is a scholar working on Information Systems, Artificial Intelligence and Management Science and Operations Research. According to data from OpenAlex, Peng Jiang has authored 58 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Information Systems, 28 papers in Artificial Intelligence and 21 papers in Management Science and Operations Research. Recurrent topics in Peng Jiang's work include Recommender Systems and Techniques (37 papers), Advanced Bandit Algorithms Research (17 papers) and Topic Modeling (12 papers). Peng Jiang is often cited by papers focused on Recommender Systems and Techniques (37 papers), Advanced Bandit Algorithms Research (17 papers) and Topic Modeling (12 papers). Peng Jiang collaborates with scholars based in China, United States and Hong Kong. Peng Jiang's co-authors include Changhua Pei, Fei Sun, Wenwu Ou, Lin Xiao, Jian Wu, Jun Liu, Shijun Li, Wenqiang Lei, Biao Li and Xiangnan He and has published in prestigious journals such as Journal of Hydrology, mBio and Euphytica.

In The Last Decade

Peng Jiang

47 papers receiving 1.9k citations

Hit Papers

align trajectories

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Peng Jiang China	18	1.5k	1.2k	476	472	135	58	2.0k
Wenwu Ou China	16	1.6k 1.1×	1.3k 1.1×	546 1.1×	454 1.0×	184 1.4×	30	2.1k
Ruiming Tang China	26	1.6k 1.0×	1.4k 1.1×	548 1.2×	483 1.0×	205 1.5×	150	2.2k
Xiuqiang He China	27	1.7k 1.1×	1.6k 1.3×	744 1.6×	463 1.0×	238 1.8×	99	2.5k
Shoujin Wang China	22	1.1k 0.7×	1.2k 1.0×	404 0.8×	270 0.6×	203 1.5×	103	1.9k
Changhua Pei China	10	1.2k 0.8×	988 0.8×	380 0.8×	339 0.7×	223 1.7×	30	1.6k
Rohan Anil United States	3	1.5k 0.9×	1.2k 0.9×	680 1.4×	281 0.6×	273 2.0×	5	2.1k
Xu Chen China	20	1.3k 0.8×	1.3k 1.1×	487 1.0×	330 0.7×	228 1.7×	121	2.1k
Vihan Jain United States	9	1.5k 1.0×	1.2k 1.0×	741 1.6×	336 0.7×	280 2.1×	12	2.2k
Hemal Shah United States	5	1.4k 0.9×	1.1k 0.9×	606 1.3×	281 0.6×	273 2.0×	7	2.1k
Ying Fan China	9	1.6k 1.0×	1.1k 0.9×	747 1.6×	374 0.8×	303 2.2×	24	2.1k

Countries citing papers authored by Peng Jiang

Since Specialization

Citations

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

Fields of papers citing papers by Peng Jiang

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peng Jiang

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

20 of 20 papers shown

1.

Ding, Y., et al.. (2025). Balancing Revenue and Privacy with Signaling Schemes in Online Ad Auctions. 512–520.

2.

Shi, Shaoyun, et al.. (2025). DAS: Dual-Aligned Semantic IDs Empowered Industrial Recommender System. 6217–6224.

3.

Xu, Yunjian, et al.. (2025). GAS: Generative Auto-bidding with Post-training Search. 315–324.

4.

Ding, Y., et al.. (2025). Optimizing Revenue through User Coupon Recommendations in Truthful Online Ad Auctions. 1380–1388.

5.

Xia, Yu, et al.. (2025). Hierarchical Tree Search-based User Lifelong Behavior Modeling on Large Language Model. 1758–1767.

6.

Liu, Ziru, Shuchang Liu, Qingpeng Cai, et al.. (2024). Modeling User Retention through Generative Flow Networks. arXiv (Cornell University). 5497–5508. 1 indexed citations

7.

Zhu, Liehuang, et al.. (2024). A Generic Blockchain-based Steganography Framework with High Capacity via Reversible GAN. 241–250. 4 indexed citations

8.

Shu, Hantao, et al.. (2024). Discrete Conditional Diffusion for Reranking in Recommendation. 161–169. 3 indexed citations

9.

Jiang, Peng, et al.. (2024). MMGCL: Meta Knowledge-Enhanced Multi-view Graph Contrastive Learning for Recommendations. 538–548. 2 indexed citations

10.

Tang, Jiakai, Sunhao Dai, Xu Chen, et al.. (2024). Towards Robust Recommendation via Decision Boundary-aware Graph Contrastive Learning. arXiv (Cornell University). 2854–2865. 4 indexed citations

11.

Li, Yan, et al.. (2024). Spatiotemporal Fine-grained Video Description for Short Videos. 3945–3954.

12.

Zhang, Zijian, Shuchang Liu, Jiaao Yu, et al.. (2024). M ³ oE: Multi-Domain Multi-Task Mixture-of Experts Recommendation Framework. arXiv (Cornell University). 893–902. 12 indexed citations

13.

Li, Biao, et al.. (2023). Disentangled Causal Embedding With Contrastive Learning For Recommender System. 406–410. 10 indexed citations

14.

Liu, Shuchang, Qingpeng Cai, Peng Jiang, et al.. (2023). Exploration and Regularization of the Latent Action Space in Recommendation. arXiv (Cornell University). 833–844. 15 indexed citations

15.

Liu, Ziru, Qingpeng Cai, Xiangyu Zhao, et al.. (2023). Multi-Task Recommendations with Reinforcement Learning. arXiv (Cornell University). 1273–1282. 23 indexed citations

16.

Ma, Weizhi, et al.. (2023). Measuring Item Global Residual Value for Fair Recommendation. 269–278. 2 indexed citations

17.

Gao, Chongming, Jiawei Chen, Yuan Zhang, et al.. (2023). Alleviating Matthew Effect of Offline Reinforcement Learning in Interactive Recommendation. arXiv (Cornell University). 238–248. 28 indexed citations

18.

Cai, Qingpeng, et al.. (2023). Two-Stage Constrained Actor-Critic for Short Video Recommendation. Rare & Special e-Zone (The Hong Kong University of Science and Technology). 865–875. 22 indexed citations

19.

Cai, Qingpeng, et al.. (2023). Reinforcing User Retention in a Billion Scale Short Video Recommender System. 421–426. 11 indexed citations

20.

Cai, Qingpeng, Shuo Sun, Shuchang Liu, et al.. (2023). PrefRec: Recommender Systems with Human Preferences for Reinforcing Long-term User Engagement. 2874–2884. 8 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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