Shengjia Zhao

1.9k total citations · 1 hit paper
25 papers, 495 citations indexed

About

Shengjia Zhao is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Signal Processing. According to data from OpenAlex, Shengjia Zhao has authored 25 papers receiving a total of 495 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 10 papers in Computer Vision and Pattern Recognition and 5 papers in Signal Processing. Recurrent topics in Shengjia Zhao's work include Generative Adversarial Networks and Image Synthesis (8 papers), Adversarial Robustness in Machine Learning (4 papers) and Machine Learning and Algorithms (3 papers). Shengjia Zhao is often cited by papers focused on Generative Adversarial Networks and Image Synthesis (8 papers), Adversarial Robustness in Machine Learning (4 papers) and Machine Learning and Algorithms (3 papers). Shengjia Zhao collaborates with scholars based in United States, China and Japan. Shengjia Zhao's co-authors include Stefano Ermon, Jiaming Song, Rui Li, Zhen Zhang, Chaomei Fu, Xia Lin, Shasha Yang, Maoyuan Jiang, Song Qin and Jinming Zhang and has published in prestigious journals such as Journal of Ethnopharmacology, The International Journal of Robotics Research and Communications Physics.

In The Last Decade

Shengjia Zhao

23 papers receiving 480 citations

Hit Papers

An “essential herbal medicine”—licorice: A review of phyt... 2019 2026 2021 2023 2019 50 100 150 200
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. An “essential herbal medicine”—licorice: A review of phytochemicals and its effects in combination preparations
    2019 217 citations Maoyuan Jiang, Shengjia Zhao et al. Journal of Ethnopharmacology profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Shengjia Zhao United States 9 175 162 119 114 39 25 495
Wenjia Wang China 13 44 0.3× 104 0.6× 129 1.1× 41 0.4× 28 0.7× 61 500
Miao Qiao China 16 44 0.3× 147 0.9× 105 0.9× 191 1.7× 22 0.6× 53 646
Junwei Luo China 18 53 0.3× 263 1.6× 679 5.7× 198 1.7× 15 0.4× 73 1.2k
Haiyang Fang China 12 38 0.2× 216 1.3× 91 0.8× 22 0.2× 32 0.8× 24 673
Xudong Zhang China 14 33 0.2× 129 0.8× 195 1.6× 56 0.5× 7 0.2× 45 629
Archit Gupta India 10 27 0.2× 191 1.2× 57 0.5× 50 0.4× 41 1.1× 52 815
Md. Mahadi Hassan Bangladesh 10 71 0.4× 71 0.4× 52 0.4× 16 0.1× 79 2.0× 24 427
Ghulam Murtaza Pakistan 15 17 0.1× 402 2.5× 160 1.3× 163 1.4× 22 0.6× 33 1.0k
Limin Sun China 15 24 0.1× 93 0.6× 100 0.8× 27 0.2× 31 0.8× 62 796

Countries citing papers authored by Shengjia Zhao

Since Specialization
Citations

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

Fields of papers citing papers by Shengjia Zhao

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shengjia Zhao

This figure shows the co-authorship network connecting the top 25 collaborators of Shengjia Zhao. A scholar is included among the top collaborators of Shengjia Zhao 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 Shengjia Zhao. Shengjia Zhao 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.
Zhao, Shengjia, et al.. (2024). Online Distribution Shift Detection via Recency Prediction. 13. 16251–16263. 1 indexed citations
2.
Zhao, Shengjia, et al.. (2023). Sample-efficient safety assurances using conformal prediction. The International Journal of Robotics Research. 43(9). 1409–1424. 5 indexed citations
3.
Jahani, Eaman, et al.. (2023). Implications of COVID-19 vaccination heterogeneity in mobility networks. Communications Physics. 6(1). 5 indexed citations
4.
Jiang, Maoyuan, Shengjia Zhao, Xia Lin, et al.. (2022). Corrigendum to “An “essential herbal medicine”—licorice: A review of phytochemicals and its effects in combination preparations” [J. Ethnopharmacol. 249 (2020) 112439]. Journal of Ethnopharmacology. 299. 115706–115706. 5 indexed citations
5.
Zhao, Shengjia, et al.. (2021). Reliable Decisions with Threshold Calibration. Neural Information Processing Systems. 34. 8 indexed citations
6.
Meng, Chenlin, Jiaming Song, Yang Song, Shengjia Zhao, & Stefano Ermon. (2021). Improved Autoregressive Modeling with Distribution Smoothing. arXiv (Cornell University). 2 indexed citations
7.
Zhao, Shengjia, et al.. (2020). Impact of Traffic Exposure and Land Use Patterns on the Risk of COVID-19 Spread at the Community Level. Zhongguo gonglu xuebao. 33(11). 43–54. 3 indexed citations
8.
Ren, Hongyu, Shengjia Zhao, & Stefano Ermon. (2019). Adaptive Antithetic Sampling for Variance Reduction. International Conference on Machine Learning. 5420–5428. 2 indexed citations
9.
Kim, Kun Ho, et al.. (2019). Cross Domain Imitation Learning. arXiv (Cornell University). 1 indexed citations
10.
Jiang, Maoyuan, Shengjia Zhao, Shasha Yang, et al.. (2019). An “essential herbal medicine”—licorice: A review of phytochemicals and its effects in combination preparations. Journal of Ethnopharmacology. 249. 112439–112439. 217 indexed citations breakdown →
11.
Song, Jiaming, et al.. (2019). Domain Adaptive Imitation Learning. arXiv (Cornell University). 1. 5286–5295. 2 indexed citations
12.
Shu, Rui, Shengjia Zhao, & Mykel J. Kochenderfer. (2018). Rethinking Style and Content Disentanglement in Variational Autoencoders. International Conference on Learning Representations. 3 indexed citations
13.
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
14.
Zhao, Shengjia, Jiaming Song, & Stefano Ermon. (2018). A Lagrangian Perspective on Latent Variable Generative Models. Uncertainty in Artificial Intelligence. 1031–1041. 1 indexed citations
15.
Shu, Rui, Hung Bui, Shengjia Zhao, Mykel J. Kochenderfer, & Stefano Ermon. (2018). Amortized Inference Regularization. Neural Information Processing Systems. 31. 4393–4402. 8 indexed citations
16.
Zhao, Shengjia, Jiaming Song, & Stefano Ermon. (2017). Learning Hierarchical Features from Deep Generative Models. International Conference on Machine Learning. 4091–4099. 37 indexed citations
17.
Song, Jiaming, Shengjia Zhao, & Stefano Ermon. (2017). Generative Adversarial Learning of Markov Chains. International Conference on Learning Representations.
18.
Song, Jiaming, Shengjia Zhao, & Stefano Ermon. (2017). A-NICE-MC: Adversarial Training for MCMC. arXiv (Cornell University). 30. 5140–5150. 16 indexed citations
19.
Zhao, Shengjia, Enze Zhou, Ashish Sabharwal, & Stefano Ermon. (2016). Adaptive Concentration Inequalities for Sequential Decision Problems. Neural Information Processing Systems. 29. 1343–1351. 11 indexed citations
20.
Zhao, Shengjia, et al.. (2016). Closing the Gap Between Short and Long XORs for Model Counting. Proceedings of the AAAI Conference on Artificial Intelligence. 30(1). 4 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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