Jiaming Song

4.1k total citations · 1 hit paper
82 papers, 729 citations indexed

About

Jiaming Song is a scholar working on Artificial Intelligence, Materials Chemistry and Electrical and Electronic Engineering. According to data from OpenAlex, Jiaming Song has authored 82 papers receiving a total of 729 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 22 papers in Materials Chemistry and 18 papers in Electrical and Electronic Engineering. Recurrent topics in Jiaming Song's work include Advanced Photocatalysis Techniques (8 papers), Generative Adversarial Networks and Image Synthesis (8 papers) and 2D Materials and Applications (7 papers). Jiaming Song is often cited by papers focused on Advanced Photocatalysis Techniques (8 papers), Generative Adversarial Networks and Image Synthesis (8 papers) and 2D Materials and Applications (7 papers). Jiaming Song collaborates with scholars based in China, United States and Germany. Jiaming Song's co-authors include Stefano Ermon, Feng Teng, Arash Vahdat, Umar Iqbal, Ye Yuan, Jan Kautz, Yunzhu Li, Haibo Fan, Peng Hu and Shengjia Zhao and has published in prestigious journals such as SHILAP Revista de lepidopterología, ACS Nano and Applied Physics Letters.

In The Last Decade

Jiaming Song

72 papers receiving 703 citations

Hit Papers

PhysDiff: Physics-Guided Human Motion Diffusion Model 2023 2026 2024 2025 2023 25 50 75
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. PhysDiff: Physics-Guided Human Motion Diffusion Model
    2023 98 citations Jiaming Song et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jiaming Song China 14 215 192 164 159 121 82 729
Xinyuan Liu China 15 107 0.5× 164 0.9× 94 0.6× 329 2.1× 76 0.6× 92 811
Zhiqiang Fu China 17 232 1.1× 402 2.1× 202 1.2× 208 1.3× 37 0.3× 40 940
Qing Yan China 16 159 0.7× 83 0.4× 141 0.9× 323 2.0× 90 0.7× 82 859
Dongdong Yu China 17 197 0.9× 87 0.5× 357 2.2× 321 2.0× 145 1.2× 50 1.4k
Guifang Shao China 19 88 0.4× 403 2.1× 79 0.5× 135 0.8× 54 0.4× 88 963
Yilin Wang China 22 167 0.8× 84 0.4× 175 1.1× 859 5.4× 76 0.6× 91 1.5k
Chunli Zhu China 17 374 1.7× 127 0.7× 45 0.3× 90 0.6× 98 0.8× 41 1.1k
Chi Guo China 20 265 1.2× 234 1.2× 156 1.0× 770 4.8× 44 0.4× 119 1.7k
Chenyang Zhao China 15 189 0.9× 125 0.7× 67 0.4× 136 0.9× 73 0.6× 77 781

Countries citing papers authored by Jiaming Song

Since Specialization
Citations

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

Fields of papers citing papers by Jiaming Song

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jiaming Song

This figure shows the co-authorship network connecting the top 25 collaborators of Jiaming Song. A scholar is included among the top collaborators of Jiaming Song 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 Jiaming Song. Jiaming Song 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.
Song, Jiaming, et al.. (2025). Structure–property relationships of ionic poly(ethylene terephthalate) (PET): effect of ion content and species. Polymer Chemistry. 16(10). 1197–1207. 1 indexed citations
2.
3.
Kong, Zheng, et al.. (2025). Range-resolved tunable diode laser absorption spectroscopy for humidity sensing. Sensors and Actuators B Chemical. 446. 138676–138676.
4.
Chen, Zongqi, Gong Feng, Jiaming Song, & Kai Zhang. (2025). Interpretable prediction of biomass-derived biochar characteristics: combining machine learning with shapley additive explanation. Energy. 335. 137877–137877. 1 indexed citations
5.
Bai, Jiaming, Cheng Luo, Kang Lu, et al.. (2025). Mechanical properties and fracture characteristics of a typical hard-to-deform superalloy GH4079 prepared by powder metallurgy technology. Journal of Materials Research and Technology. 39. 6254–6262.
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Song, Jiaming, et al.. (2024). Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(10). 11320–11328. 6 indexed citations
8.
Yang, Xiaobin, Zhonghui Han, Jiaming Song, Peng Hu, & Feng Teng. (2023). Novel application of electrochemical test for the controllable electrodeposition of Cu2O and metallic Cu film. Journal of Alloys and Compounds. 970. 172706–172706. 3 indexed citations
9.
Song, Jiaming, Xiaojuan Wang, Mingshu He, & Lei Jin. (2023). CSK-CNN: Network Intrusion Detection Model Based on Two-Layer Convolution Neural Network for Handling Imbalanced Dataset. Information. 14(2). 130–130. 10 indexed citations
10.
Li, Daming, et al.. (2022). Trade Flow Optimization Model for Plastic Pollution Reduction. International Journal of Environmental Research and Public Health. 19(23). 15963–15963. 2 indexed citations
11.
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Song, Yang, et al.. (2021). Imitation with Neural Density Models. Neural Information Processing Systems. 34. 3 indexed citations
13.
Markevich, Alexander, Bethany M. Hudak, Jacob Madsen, et al.. (2021). Mechanism of Electron-Beam Manipulation of Single-Dopant Atoms in Silicon. The Journal of Physical Chemistry C. 125(29). 16041–16048. 11 indexed citations
14.
Sinha, Abhishek, Jiaming Song, Chenlin Meng, & Stefano Ermon. (2021). D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation. Neural Information Processing Systems. 34. 32 indexed citations
15.
Grover, Aditya, Jiaming Song, Ashish Kapoor, et al.. (2019). Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting. arXiv (Cornell University). 32. 11056–11068. 6 indexed citations
16.
Song, Jiaming, et al.. (2018). Malicious behaviour classification in web logs based on an improved Xgboost algorithm. International Journal of Web Engineering and Technology. 13(4). 334–334.
17.
Zhao, Shengjia, Hongyu Ren, Arianna Yuan, et al.. (2018). Bias and Generalization in Deep Generative Models: An Empirical Study. arXiv (Cornell University). 31. 10792–10801. 7 indexed citations
18.
Song, Jiaming, Hongyu Ren, Dorsa Sadigh, & Stefano Ermon. (2018). Multi-Agent Generative Adversarial Imitation Learning. arXiv (Cornell University). 31. 7461–7472. 25 indexed citations
19.
Li, Yunzhu, Jiaming Song, & Stefano Ermon. (2017). InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations. Neural Information Processing Systems. 30. 3812–3822. 47 indexed citations
20.
Li, Yunzhu, Jiaming Song, & Stefano Ermon. (2017). Inferring The Latent Structure of Human Decision-Making from Raw Visual Inputs. arXiv (Cornell University). 3813–3823. 1 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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