Shen Yan

503 total citations · 1 hit paper
9 papers, 225 citations indexed

About

Shen Yan is a scholar working on Experimental and Cognitive Psychology, Artificial Intelligence and Social Psychology. According to data from OpenAlex, Shen Yan has authored 9 papers receiving a total of 225 indexed citations (citations by other indexed papers that have themselves been cited), including 4 papers in Experimental and Cognitive Psychology, 3 papers in Artificial Intelligence and 2 papers in Social Psychology. Recurrent topics in Shen Yan's work include Mental Health Research Topics (4 papers), Emotion and Mood Recognition (2 papers) and Digital Mental Health Interventions (2 papers). Shen Yan is often cited by papers focused on Mental Health Research Topics (4 papers), Emotion and Mood Recognition (2 papers) and Digital Mental Health Interventions (2 papers). Shen Yan collaborates with scholars based in United States, China and Germany. Shen Yan's co-authors include Emilio Ferrara, A. Salman Avestimehr, Chaoyang He, Mohammad Soleymani, Di Huang, Kristina Lerman, Shrikanth Narayanan, Homa Hosseinmardi, Wenxi Wang and Hao Wang and has published in prestigious journals such as Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies, Plant Communications and PubMed.

In The Last Decade

Shen Yan

9 papers receiving 217 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.

FairFed: Enabling Group Fairness in Federated Learning

2023 95 citations Shen Yan, Chaoyang He et al. Proceedings of the AAAI Conference on Artificial Intelligence profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Shen Yan United States	7	134	71	26	22	21	9	225
Larry Chan United States	5	183 1.4×	62 0.9×	22 0.8×	40 1.8×	27 1.3×	7	298
Marcelo Prates Brazil	2	111 0.8×	43 0.6×	12 0.5×	13 0.6×	15 0.7×	5	190
Matthias Kraus Germany	10	187 1.4×	27 0.4×	24 0.9×	5 0.2×	17 0.8×	26	270
Hanxiang Du United States	9	48 0.4×	12 0.2×	5 0.2×	8 0.4×	26 1.2×	24	214
Marjan Ghazi Saeedi Iran	4	162 1.2×	7 0.1×	15 0.6×	24 1.1×	8 0.4×	10	319
Patrick McDonagh Ireland	9	52 0.4×	24 0.3×	32 1.2×	3 0.1×	72 3.4×	25	207
Mor Vered Australia	8	135 1.0×	24 0.3×	26 1.0×	39 1.8×	6 0.3×	24	219
Christina Sanchez‐Stockhammer Germany	5	66 0.5×	5 0.1×	15 0.6×	7 0.3×	6 0.3×	8	176
Luca Guarnera Italy	9	78 0.6×	11 0.2×	199 7.7×	8 0.4×	15 0.7×	18	307
Minae Kwon United States	7	92 0.7×	26 0.4×	11 0.4×	2 0.1×	17 0.8×	8	150

Countries citing papers authored by Shen Yan

Since Specialization

Citations

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

Fields of papers citing papers by Shen Yan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shen Yan

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

9 of 9 papers shown

1.

Wang, Hao, Shen Yan, Wenxi Wang, et al.. (2024). Cropformer: An interpretable deep learning framework for crop genomic prediction. Plant Communications. 6(3). 101223–101223. 18 indexed citations

2.

Yan, Shen, et al.. (2023). FairFed: Enabling Group Fairness in Federated Learning. Proceedings of the AAAI Conference on Artificial Intelligence. 37(6). 7494–7502. 95 indexed citations breakdown →

3.

Yan, Shen, et al.. (2021). Mitigating the Bias of Heterogeneous Human Behavior in Affective Computing. 1–8. 6 indexed citations

4.

Yan, Shen, et al.. (2020). User-Based Collaborative Filtering Mobile Health System. Proceedings of the ACM on Interactive Mobile Wearable and Ubiquitous Technologies. 4(4). 1–17. 8 indexed citations

5.

Yan, Shen, et al.. (2020). Affect Estimation with Wearable Sensors. PubMed. 4(3). 261–294. 8 indexed citations

6.

Yan, Shen, Di Huang, & Mohammad Soleymani. (2020). Mitigating Biases in Multimodal Personality Assessment. 361–369. 36 indexed citations

7.

Yan, Shen, et al.. (2020). Fair Class Balancing: Enhancing Model Fairness without Observing Sensitive Attributes. 1715–1724. 45 indexed citations

8.

Yan, Shen, et al.. (2019). Estimating Individualized Daily Self-Reported Affect with Wearable Sensors. 1–9. 5 indexed citations

9.

Hosseinmardi, Homa, et al.. (2018). Discovering Latent Psychological Structures from Self-Report Assessments of Hospital Workers. 19. 156–161. 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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