Jianfeng Chi

893 total citations · 1 hit paper
22 papers, 429 citations indexed

About

Jianfeng Chi is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Sociology and Political Science. According to data from OpenAlex, Jianfeng Chi has authored 22 papers receiving a total of 429 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 4 papers in Electrical and Electronic Engineering and 3 papers in Sociology and Political Science. Recurrent topics in Jianfeng Chi's work include Adversarial Robustness in Machine Learning (5 papers), Imbalanced Data Classification Techniques (5 papers) and Topic Modeling (4 papers). Jianfeng Chi is often cited by papers focused on Adversarial Robustness in Machine Learning (5 papers), Imbalanced Data Classification Techniques (5 papers) and Topic Modeling (4 papers). Jianfeng Chi collaborates with scholars based in United States, China and Germany. Jianfeng Chi's co-authors include Jinghua Feng, Xiang Ao, Hao Yang, Qing He, Yang Liu, Kai-Wei Chang, Wasi Uddin Ahmad, Yuan Tian, Kuan Li and Jiayu Tang and has published in prestigious journals such as Chinese Physics Letters, arXiv (Cornell University) and Proceedings of the ACM Web Conference 2022.

In The Last Decade

Jianfeng Chi

21 papers receiving 418 citations

Hit Papers

align trajectories

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.

Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection

2021 204 citations Yang Liu, Xiang Ao et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jianfeng Chi United States	8	359	137	59	57	37	22	429
Jeff Pasternack United States	7	279 0.8×	152 1.1×	44 0.7×	61 1.1×	20 0.5×	7	415
Sanasam Ranbir Singh India	10	223 0.6×	66 0.5×	36 0.6×	40 0.7×	34 0.9×	61	326
Feifei Kou China	10	173 0.5×	76 0.6×	17 0.3×	22 0.4×	71 1.9×	31	262
Paolo Tomeo Italy	8	184 0.5×	257 1.9×	44 0.7×	22 0.4×	63 1.7×	15	315
Zhiyang Teng China	12	517 1.4×	61 0.4×	12 0.2×	15 0.3×	75 2.0×	25	640
Tung Mai United States	7	123 0.3×	47 0.3×	36 0.6×	9 0.2×	40 1.1×	18	242
Todor Mihaylov Germany	11	518 1.4×	156 1.1×	17 0.3×	104 1.8×	142 3.8×	17	621
Shuyuan Xu United States	13	295 0.8×	261 1.9×	33 0.6×	24 0.4×	49 1.3×	33	431
Jörg Diederich Germany	7	151 0.4×	184 1.3×	120 2.0×	27 0.5×	25 0.7×	12	265
Xuezhi Cao China	10	300 0.8×	241 1.8×	39 0.7×	23 0.4×	84 2.3×	21	408

Countries citing papers authored by Jianfeng Chi

Since Specialization

Citations

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

Fields of papers citing papers by Jianfeng Chi

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jianfeng Chi

This figure shows the co-authorship network connecting the top 25 collaborators of Jianfeng Chi. A scholar is included among the top collaborators of Jianfeng Chi 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 Chi. Jianfeng Chi 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.

Zhao, Han, et al.. (2025). Towards Understanding the Fragility of Multilingual LLMs against Fine-Tuning Attacks. 2358–2372. 1 indexed citations

2.

Zhang, Jinghuai, et al.. (2024). Where Have You Been? A Study of Privacy Risk for Point-of-Interest Recommendation. 175–186. 1 indexed citations

3.

Zhang, Jinghuai, et al.. (2024). BadMerging: Backdoor Attacks Against Model Merging. 4450–4464. 3 indexed citations

4.

Wang, Qifan, Jianfeng Chi, Jingang Wang, et al.. (2024). EAVE: Efficient Product Attribute Value Extraction via Lightweight Sparse-layer Interaction. 1491–1505. 1 indexed citations

5.

Chi, Jianfeng, Wasi Uddin Ahmad, Yuan Tian, & Kai-Wei Chang. (2023). PLUE: Language Understanding Evaluation Benchmark for Privacy Policies in English. 5 indexed citations

6.

Chi, Jianfeng, et al.. (2023). Retrieval Enhanced Data Augmentation for Question Answering on Privacy Policies. 201–210. 2 indexed citations

7.

Chi, Jianfeng, et al.. (2022). Conditional Supervised Contrastive Learning for Fair Text Classification. 2736–2756. 6 indexed citations

8.

Liu, Yang, Xiang Ao, Kuan Li, et al.. (2022). AUC-oriented Graph Neural Network for Fraud Detection. Proceedings of the ACM Web Conference 2022. 1311–1321. 55 indexed citations

9.

Chi, Jianfeng, et al.. (2022). Reliable Representations Make A Stronger Defender. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 925–935. 33 indexed citations

10.

Chi, Jianfeng, Han Zhao, Geoff Gordon, & Yuan Tian. (2021). Understanding and Mitigating Accuracy Disparity in Regression. International Conference on Machine Learning. 1866–1876. 3 indexed citations

11.

Liang, Ting, et al.. (2021). Credit Risk and Limits Forecasting in E-Commerce Consumer Lending Service via Multi-view-aware Mixture-of-experts Nets. 229–237. 30 indexed citations

12.

Liu, Yang, Xiang Ao, Jianfeng Chi, et al.. (2021). Pick and Choose: A GNN-based Imbalanced Learning Approach for Fraud Detection. 3168–3177. 204 indexed citations breakdown →

13.

Ahmad, Wasi Uddin, Jianfeng Chi, Yuan Tian, & Kai-Wei Chang. (2020). PolicyQA: A Reading Comprehension Dataset for Privacy Policies. 743–749. 29 indexed citations

14.

Chi, Jianfeng, et al.. (2020). Learning to Undersampling for Class Imbalanced Credit Risk Forecasting. 72–81. 13 indexed citations

15.

Zhao, Han, et al.. (2019). Adversarial Task-Specific Privacy Preservation under Attribute Attack.. arXiv (Cornell University). 1 indexed citations

16.

Zhao, Han, Jianfeng Chi, Yuan Tian, & Geoffrey J. Gordon. (2019). Adversarial Privacy Preservation under Attribute Inference Attack. 2 indexed citations

17.

Liu, Sihang, et al.. (2019). Side Channel Attacks in Computation Offloading Systems with GPU Virtualization. 156–161. 4 indexed citations

18.

Chi, Jianfeng, Emmanuel Owusu, Xuwang Yin, et al.. (2018). Privacy Partition: A Privacy-Preserving Framework for Deep Neural Networks in Edge Networks. 378–380. 15 indexed citations

19.

Zhong, Kangping, et al.. (2010). Experimental study on temperature dependence of dispersion of G.652 fiber and its effect on high speed optical communication system and compensation. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7847. 78472N–78472N. 3 indexed citations

20.

Zhong, Kangping, et al.. (2010). A Clock Enhanced Loop for Simultaneous Error-Free Demultiplexing and Clock Recovery of 160 Gb/s OTDM Signal Single-Channel Transmission over 100 km. Chinese Physics Letters. 27(11). 114213–114213. 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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