Fenglong Ma

5.6k total citations · 2 hit papers
120 papers, 3.5k citations indexed

About

Fenglong Ma is a scholar working on Artificial Intelligence, Information Systems and Health Information Management. According to data from OpenAlex, Fenglong Ma has authored 120 papers receiving a total of 3.5k indexed citations (citations by other indexed papers that have themselves been cited), including 86 papers in Artificial Intelligence, 23 papers in Information Systems and 22 papers in Health Information Management. Recurrent topics in Fenglong Ma's work include Topic Modeling (42 papers), Machine Learning in Healthcare (30 papers) and Artificial Intelligence in Healthcare (20 papers). Fenglong Ma is often cited by papers focused on Topic Modeling (42 papers), Machine Learning in Healthcare (30 papers) and Artificial Intelligence in Healthcare (20 papers). Fenglong Ma collaborates with scholars based in United States, China and Hong Kong. Fenglong Ma's co-authors include Jing Gao, Lü Su, Ye Yuan, Yaqing Wang, Guangxu Xun, Aidong Zhang, Kishlay Jha, Zhiwei Jin, Cao Xiao and Muchao Ye and has published in prestigious journals such as Expert Systems with Applications, Sensors and BMC Bioinformatics.

In The Last Decade

Fenglong Ma

109 papers receiving 3.4k citations

Hit Papers

EANN 2018 2026 2020 2023 2018 2018 200 400 600
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. EANN
    2018 668 citations Yaqing Wang, Fenglong Ma et al. profile →
  2. Towards Environment Independent Device Free Human Activity Recognition
    2018 417 citations Fenglong Ma, Ye Yuan et al. profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Fenglong Ma 2.1k 860 857 539 532 120 3.5k
Jie Yin 1.7k 0.8× 511 0.6× 403 0.5× 583 1.1× 713 1.3× 98 3.6k
Young-Koo Lee 1.5k 0.7× 1.3k 1.6× 224 0.3× 623 1.2× 391 0.7× 279 4.1k
Rahul Katarya 1.0k 0.5× 715 0.8× 257 0.3× 183 0.3× 81 0.2× 142 2.3k
Zhiping Cai 1.8k 0.9× 713 0.8× 99 0.1× 344 0.6× 901 1.7× 229 4.5k
Chang-Shing Lee 1.5k 0.7× 766 0.9× 142 0.2× 265 0.5× 54 0.1× 135 2.5k
Hongxia Jin 1.3k 0.6× 534 0.6× 501 0.6× 417 0.8× 146 0.3× 149 2.2k
Kuan-Ta Chen 522 0.3× 668 0.8× 488 0.6× 341 0.6× 257 0.5× 99 3.1k
Irina Rish 1.5k 0.7× 611 0.7× 64 0.1× 351 0.7× 209 0.4× 84 3.5k
Yi Mu 4.5k 2.1× 3.1k 3.6× 228 0.3× 209 0.4× 468 0.9× 385 6.0k

Countries citing papers authored by Fenglong Ma

Since Specialization
Citations

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

Fields of papers citing papers by Fenglong Ma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fenglong Ma

This figure shows the co-authorship network connecting the top 25 collaborators of Fenglong Ma. A scholar is included among the top collaborators of Fenglong Ma 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 Fenglong Ma. Fenglong Ma 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.
Liu, Jinduo, et al.. (2025). Brain Effective Connectivity Estimation via Fourier Spatiotemporal Attention. 1657–1668. 1 indexed citations
2.
Zhang, Xiaokun, et al.. (2025). Rethinking contrastive learning in session-based recommendation. Pattern Recognition. 169. 111924–111924. 1 indexed citations
3.
Zhang, Xiaokun, Bo Xu, Chenliang Li, et al.. (2025). A Survey on Side Information-Driven Session-Based Recommendation: From a Data-Centric Perspective. IEEE Transactions on Knowledge and Data Engineering. 37(8). 4411–4431.
4.
5.
Zhong, Yuan, Jiaqi Wang, Xiaochen Wang, et al.. (2024). MedDiffusion: Boosting Health Risk Prediction via Diffusion-based Data Augmentation. Society for Industrial and Applied Mathematics eBooks. 2024. 499–507. 5 indexed citations
6.
Liu, Han, Xiaotong Zhang, Feng Zhang, et al.. (2024). Depression Detection via Capsule Networks with Contrastive Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 38(20). 22231–22239. 3 indexed citations
7.
Zhang, Xiaokun, et al.. (2024). Disentangling ID and Modality Effects for Session-based Recommendation. arXiv (Cornell University). 1883–1892. 8 indexed citations
8.
Zhang, Xiaokun, et al.. (2024). FineRec: Exploring Fine-grained Sequential Recommendation. arXiv (Cornell University). 1599–1608. 8 indexed citations
9.
Liu, Han, Xiaotong Zhang, Qimai Li, et al.. (2023). Boosting Decision-Based Black-Box Adversarial Attack with Gradient Priors. 1195–1203. 1 indexed citations
10.
Lin, Hongfei, Xiaokun Zhang, Zhaoqing Li, et al.. (2023). Hate Speech Detection via Dual Contrastive Learning. IEEE/ACM Transactions on Audio Speech and Language Processing. 31. 2787–2795. 16 indexed citations
11.
Zhang, Xiaokun, Bo Xu, Fenglong Ma, et al.. (2023). Bi-preference Learning Heterogeneous Hypergraph Networks for Session-based Recommendation. ACM Transactions on Information Systems. 42(3). 1–28. 11 indexed citations
12.
Zhang, Xiaokun, Bo Xu, Fenglong Ma, et al.. (2023). Beyond Co-Occurrence: Multi-Modal Session-Based Recommendation. IEEE Transactions on Knowledge and Data Engineering. 36(4). 1450–1462. 22 indexed citations
13.
Ma, Fenglong, et al.. (2023). Who Gets the Flu? Individualized Validation of Influenza-like Illness in Urban Spaces. International Journal of Environmental Research and Public Health. 20(10). 5865–5865. 2 indexed citations
14.
Liu, Han, Xiaoming Xu, Feng Zhang, et al.. (2023). SSPAttack: A Simple and Sweet Paradigm for Black-Box Hard-Label Textual Adversarial Attack. Proceedings of the AAAI Conference on Artificial Intelligence. 37(11). 13228–13235. 7 indexed citations
15.
Wang, Jiaqi, et al.. (2022). AUTOMED: Automated Medical Risk Predictive Modeling on Electronic Health Records. 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). 2022. 948–953. 2 indexed citations
16.
Lin, Chi, et al.. (2019). Minimizing Charging Delay for Directional Charging in Wireless Rechargeable Sensor Networks. 1819–1827. 74 indexed citations
17.
Wang, Tianqi, Fenglong Ma, & Jing Gao. (2019). Deep Hierarchical Knowledge Tracing. Educational Data Mining. 671–674. 12 indexed citations
18.
Xiao, Houping, Jing Gao, Qi Li, et al.. (2018). Towards Confidence Interval Estimation in Truth Discovery. IEEE Transactions on Knowledge and Data Engineering. 31(3). 575–588. 17 indexed citations
19.
Suo, Qiuling, Fenglong Ma, Ye Yuan, et al.. (2018). Deep Patient Similarity Learning for Personalized Healthcare. IEEE Transactions on NanoBioscience. 17(3). 219–227. 94 indexed citations
20.
Yuan, Ye, Kebin Jia, Fenglong Ma, et al.. (2018). Multivariate Sleep Stage Classification using Hybrid Self-Attentive Deep Learning Networks. 963–968. 15 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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