Stephen S.‐T. Yau

8.3k total citations · 1 hit paper
343 papers, 4.7k citations indexed

About

Stephen S.‐T. Yau is a scholar working on Geometry and Topology, Artificial Intelligence and Applied Mathematics. According to data from OpenAlex, Stephen S.‐T. Yau has authored 343 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 106 papers in Geometry and Topology, 74 papers in Artificial Intelligence and 62 papers in Applied Mathematics. Recurrent topics in Stephen S.‐T. Yau's work include Algebraic Geometry and Number Theory (52 papers), Target Tracking and Data Fusion in Sensor Networks (51 papers) and Machine Learning in Bioinformatics (44 papers). Stephen S.‐T. Yau is often cited by papers focused on Algebraic Geometry and Number Theory (52 papers), Target Tracking and Data Fusion in Sensor Networks (51 papers) and Machine Learning in Bioinformatics (44 papers). Stephen S.‐T. Yau collaborates with scholars based in China, United States and Hong Kong. Stephen S.‐T. Yau's co-authors include Stephen C.K. Law, Sin‐Ming Chow, Siu‐Kie Au, Rong He, Wai‐Hon Lau, Changchuan Yin, John K. Chan, Shing‐Tung Yau, Chenglong Yu and Huaiqing Zuo and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Clinical Oncology.

In The Last Decade

Stephen S.‐T. Yau

293 papers receiving 4.3k 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.

Papillary microcarcinoma of the thyroid—Prognostic significance of lymph node metastasis and multifocality

2003 572 citations Stephen S.‐T. Yau et al. profile →

Peers

Stephen S.‐T. Yau

MB

EDM

GT

SURGE

AI

Hans G. Feichtinger Austria

Clyde F. Martin United States

JinRong Wang China

David F. Anderson United States

Pascal Massart France

Giuseppe Modica Italy

Larry Goldstein United States

Rolf Schneider Germany

G. Adomian United States

De-Xing Kong China

Hans G. Feichtinger Austria

Stephen S.‐T. Yau

1.3k ×1.3

MB

409 ×0.5

EDM

69 ×0.1

GT

889 ×1.1

SURGE

144 ×0.2

AI

Citations per year, relative to Stephen S.‐T. Yau Stephen S.‐T. Yau (= 1×) peers Hans G. Feichtinger

Countries citing papers authored by Stephen S.‐T. Yau

Since Specialization

Citations

This map shows the geographic impact of Stephen S.‐T. Yau'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 Stephen S.‐T. Yau with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Stephen S.‐T. Yau more than expected).

Fields of papers citing papers by Stephen S.‐T. Yau

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Stephen S.‐T. Yau. 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 Stephen S.‐T. Yau. The network helps show where Stephen S.‐T. Yau may publish in the future.

Co-authorship network of co-authors of Stephen S.‐T. Yau

This figure shows the co-authorship network connecting the top 25 collaborators of Stephen S.‐T. Yau. A scholar is included among the top collaborators of Stephen S.‐T. Yau 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 Stephen S.‐T. Yau. Stephen S.‐T. Yau 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.

Yau, Stephen S.‐T., et al.. (2025). Normal surface singularities of small degrees. Journal of the Mathematical Society of Japan. 78(1).

2.

Yau, Stephen S.‐T., et al.. (2024). Geometric analysis of SARS-CoV-2 variants. Gene. 909. 148291–148291. 1 indexed citations

3.

Chen, Xiuqiong, et al.. (2024). Time-varying feedback particle filter. Automatica. 167. 111740–111740. 1 indexed citations

4.

Yau, Stephen S.‐T., et al.. (2024). Recurrent neural network spectral method and its application in stable filtering problems. Automatica. 173. 112067–112067.

5.

Yau, Stephen S.‐T., et al.. (2024). The optimal metric for viral genome space. Computational and Structural Biotechnology Journal. 23. 2083–2096.

6.

Chen, Xiuqiong, et al.. (2024). A Uniform Framework of Yau–Yau Algorithm Based on Deep Learning With the Capability of Overcoming the Curse of Dimensionality. IEEE Transactions on Automatic Control. 70(1). 339–354.

7.

Yau, Stephen S.‐T., et al.. (2023). Hessian matrix non-decomposition theorem and its application to nonlinear filtering. Nonlinear Analysis. 230. 113236–113236. 1 indexed citations

8.

Zhou, Haoyu, et al.. (2023). Utilizing the codon adaptation index to evaluate the susceptibility to HIV-1 and SARS-CoV-2 related coronaviruses in possible target cells in humans. Frontiers in Cellular and Infection Microbiology. 12. 1085397–1085397. 5 indexed citations

9.

Yau, Stephen S.‐T., et al.. (2023). Mathematical Principles in Bioinformatics.

10.

Yau, Stephen S.‐T., et al.. (2015). On the quenching behavior of the MEMS with fringing field. Quarterly of Applied Mathematics. 73(4). 629–659. 3 indexed citations

11.

Wen, Jia, Raymond H. Chan, Shek-Chung Yau, Rong He, & Stephen S.‐T. Yau. (2014). K-mer natural vector and its application to the phylogenetic analysis of genetic sequences. Gene. 546(1). 25–34. 48 indexed citations

12.

Kang, Ming-chang, et al.. (2009). Some primitive linear groups of prime degree. Journal of the Mathematical Society of Japan. 61(4).

13.

Yau, Stephen S.‐T., et al.. (2007). The diffeomorphic types of the complements of arrangements in CP 3 I: Point arrangements. Journal of the Mathematical Society of Japan. 59(2). 3 indexed citations

14.

Yau, Stephen S.‐T., et al.. (2004). Classification of Affine Varieties Being Cones over Nonsingular Projective Varieties: Hypersurface Case. Communications in Analysis and Geometry. 12(5). 1201–1219. 9 indexed citations

15.

Huang, Jimmy Xiangji, et al.. (2003). Punctured local holomorphic de Rham cohomology. Journal of the Mathematical Society of Japan. 55(3). 4 indexed citations

16.

Yau, Stephen S.‐T., et al.. (1998). Explicit construction of graph invariant for strongly pseudoconvex compact 3-dimensional rational CR manifolds. Compositio Mathematica. 114(1). 77–111. 2 indexed citations

17.

Yau, Stephen S.‐T., et al.. (1993). Topological invariance of intersection lattices of arrangements in 𝐂𝐏². Bulletin of the American Mathematical Society. 29(1). 88–93. 10 indexed citations

18.

Yau, Stephen S.‐T. & Jin-Gyun Chung. (1986). On the design of modulo arithmetic units based on cyclic groups. IEEE Press eBooks. 113–122.

19.

Singer, I. M., Bun Wong, Shing‐Tung Yau, & Stephen S.‐T. Yau. (1985). An estimate of the gap of the first two eigenvalues in the Schrödinger operator. French digital mathematics library (Numdam). 12(2). 319–333. 89 indexed citations

20.

Yau, Stephen S.‐T.. (1979). Normal Two-Dimensional Elliptic Singularities. Transactions of the American Mathematical Society. 254. 117–117. 5 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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