Bryant Chen

877 total citations
17 papers, 197 citations indexed

About

Bryant Chen is a scholar working on Artificial Intelligence, Signal Processing and Computational Theory and Mathematics. According to data from OpenAlex, Bryant Chen has authored 17 papers receiving a total of 197 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 3 papers in Signal Processing and 3 papers in Computational Theory and Mathematics. Recurrent topics in Bryant Chen's work include Bayesian Modeling and Causal Inference (9 papers), Adversarial Robustness in Machine Learning (3 papers) and Anomaly Detection Techniques and Applications (3 papers). Bryant Chen is often cited by papers focused on Bayesian Modeling and Causal Inference (9 papers), Adversarial Robustness in Machine Learning (3 papers) and Anomaly Detection Techniques and Applications (3 papers). Bryant Chen collaborates with scholars based in United States and Taiwan. Bryant Chen's co-authors include Heiko Ludwig, Nathalie Baracaldo, Judea Pearl, Rui Zhang, Elias Bareinboim, Daniel Kumor, Jin Tian, Carlos Cinelli, Adarsh Subbaswamy and Suchi Saria and has published in prestigious journals such as SHILAP Revista de lepidopterología, arXiv (Cornell University) and eScholarship (California Digital Library).

In The Last Decade

Bryant Chen

17 papers receiving 192 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Bryant Chen United States	8	125	43	40	24	23	17	197
Mark G. Kelly United Kingdom	5	182 1.5×	25 0.6×	27 0.7×	63 2.6×	12 0.5×	7	251
Huadi Zheng Hong Kong	8	281 2.2×	35 0.8×	21 0.5×	29 1.2×	8 0.3×	15	327
D. Ezhilmaran India	9	55 0.4×	26 0.6×	46 1.1×	42 1.8×	12 0.5×	46	197
Marïa José Ramírez-Quintana Spain	8	165 1.3×	7 0.2×	14 0.3×	38 1.6×	7 0.3×	28	226
Victor E. Lee United States	6	98 0.8×	33 0.8×	15 0.4×	106 4.4×	6 0.3×	8	188
J. V. R. Murthy India	9	84 0.7×	23 0.5×	18 0.5×	59 2.5×	3 0.1×	34	198
Jiahuan He China	9	82 0.7×	58 1.3×	22 0.6×	193 8.0×	8 0.3×	15	296
Md. Asraful Haque India	9	35 0.3×	16 0.4×	16 0.4×	109 4.5×	20 0.9×	27	251
Miroslav Hudec Slovakia	8	122 1.0×	39 0.9×	75 1.9×	58 2.4×	3 0.1×	43	251
Michel Manago Germany	7	150 1.2×	15 0.3×	11 0.3×	57 2.4×	5 0.2×	12	212

Countries citing papers authored by Bryant Chen

Since Specialization

Citations

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

Fields of papers citing papers by Bryant Chen

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bryant Chen

This figure shows the co-authorship network connecting the top 25 collaborators of Bryant Chen. A scholar is included among the top collaborators of Bryant Chen 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 Bryant Chen. Bryant Chen is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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17 of 17 papers shown

Subbaswamy, Adarsh, Bryant Chen, & Suchi Saria. (2022). A unifying causal framework for analyzing dataset shift-stable learning algorithms. SHILAP Revista de lepidopterología. 10(1). 64–89. 10 indexed citations

Cinelli, Carlos, et al.. (2021). Exploiting Equality Constraints in Causal Inference. International Conference on Artificial Intelligence and Statistics. 1630–1638. 2 indexed citations

Ashktorab, Zahra, Casey Dugan, James Johnson, et al.. (2021). The Design and Development of a Game to Study Backdoor Poisoning Attacks: The Backdoor Game. 423–433. 1 indexed citations

Zhang, Chi, Bryant Chen, & Judea Pearl. (2020). A Simultaneous Discover-Identify Approach to Causal Inference in Linear Models. Proceedings of the AAAI Conference on Artificial Intelligence. 34(6). 10318–10325. 4 indexed citations

Cinelli, Carlos, Daniel Kumor, Bryant Chen, Judea Pearl, & Elias Bareinboim. (2019). Sensitivity Analysis of Linear Structural Causal Models. International Conference on Machine Learning. 1252–1261. 15 indexed citations

Kumor, Daniel, Bryant Chen, & Elias Bareinboim. (2019). Efficient Identification in Linear Structural Causal Models with Instrumental Cutsets. arXiv (Cornell University). 32. 12477–12486. 1 indexed citations

Engel, R., et al.. (2018). ysla: Reusable and Configurable SLAs for Large-Scale SLA Management. 317–325. 7 indexed citations

Baracaldo, Nathalie, et al.. (2018). Detecting Poisoning Attacks on Machine Learning in IoT Environments. 57–64. 42 indexed citations

Baracaldo, Nathalie, et al.. (2017). Mitigating Poisoning Attacks on Machine Learning Models. 103–110. 65 indexed citations

10.

Engel, R., et al.. (2017). Domain-Independent Monitoring and Visualization of SLA Metrics in Multi-provider Environments - (Short Paper).. 628–638. 1 indexed citations

11.

Chen, Bryant. (2016). Identification and Overidentification of Linear Structural Equation Models. Neural Information Processing Systems. 29. 1579–1587. 3 indexed citations

12.

Chen, Bryant, Daniel Kumor, & Elias Bareinboim. (2016). Identification and Model Testing in Linear Structural Equation Models using Auxiliary Variables. arXiv (Cornell University). 757–766. 7 indexed citations

13.

Chen, Bryant, Judea Pearl, & Elias Bareinboim. (2015). Incorporating Knowledge into Structural Equation Models using Auxiliary Variables. arXiv (Cornell University). 3577–3583. 4 indexed citations

14.

Chen, Bryant, Jin Tian, & Judea Pearl. (2014). Testable Implications of Linear Structural Equation Models. Proceedings of the AAAI Conference on Artificial Intelligence. 28(1). 16 indexed citations

15.

Chen, Bryant, et al.. (2014). Linear-time accurate lattice algorithms for tail conditional expectation. 3(1-2). 87–140. 4 indexed citations

16.

Chen, Bryant & Judea Pearl. (2013). Regression and Causation: A Critical Examination of Six Econometrics Textbooks. eScholarship (California Digital Library). 14 indexed citations

17.

Chen, Bryant, William Hsu, Ming‐Yang Kao, et al.. (2009). Fast Accurate Algorithms for Tail Conditional Expectation. AIP conference proceedings. 501–504. 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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