X. Sheldon Lin

3.9k total citations
100 papers, 2.7k citations indexed

About

X. Sheldon Lin is a scholar working on Management Science and Operations Research, Statistics and Probability and Artificial Intelligence. According to data from OpenAlex, X. Sheldon Lin has authored 100 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Management Science and Operations Research, 33 papers in Statistics and Probability and 26 papers in Artificial Intelligence. Recurrent topics in X. Sheldon Lin's work include Probability and Risk Models (29 papers), Insurance, Mortality, Demography, Risk Management (25 papers) and Statistical Distribution Estimation and Applications (23 papers). X. Sheldon Lin is often cited by papers focused on Probability and Risk Models (29 papers), Insurance, Mortality, Demography, Risk Management (25 papers) and Statistical Distribution Estimation and Applications (23 papers). X. Sheldon Lin collaborates with scholars based in Canada, United States and China. X. Sheldon Lin's co-authors include Gordon E. Willmot, Steve Drekic, Hao Helen Zhang, Cheolwoo Park, Jeongyoun Ahn, Ken Seng Tan, Hailiang Yang, Andrei L. Badescu, Cindy E. Hmelo and Chris Clifton and has published in prestigious journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.

In The Last Decade

X. Sheldon Lin

97 papers receiving 2.6k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
X. Sheldon Lin Canada 27 1.3k 949 690 665 628 100 2.7k
Ludger Rüschendorf Germany 34 1.7k 1.4× 297 0.3× 1.2k 1.7× 500 0.8× 1.6k 2.5× 195 4.2k
Kai Wang Ng Hong Kong 20 839 0.7× 336 0.4× 982 1.4× 435 0.7× 644 1.0× 64 2.0k
Jean Jacod France 40 1.2k 0.9× 587 0.6× 1.4k 2.0× 485 0.7× 5.9k 9.5× 98 7.9k
Minyi Huang Canada 32 674 0.5× 285 0.3× 166 0.2× 384 0.6× 1.9k 3.0× 124 5.0k
Rama Cont United Kingdom 37 1.4k 1.1× 412 0.4× 290 0.4× 162 0.2× 4.9k 7.8× 138 6.6k
Richard L. Dykstra United States 22 484 0.4× 78 0.1× 1.5k 2.2× 591 0.9× 508 0.8× 76 3.0k
Perwez Shahabuddin United States 26 1.1k 0.9× 208 0.2× 519 0.8× 193 0.3× 453 0.7× 61 2.7k
Upendra Dave India 17 1.2k 0.9× 124 0.1× 688 1.0× 291 0.4× 342 0.5× 53 3.7k
Ken‐iti Sato Japan 19 787 0.6× 231 0.2× 616 0.9× 177 0.3× 2.2k 3.5× 71 3.4k
Sergey Foss Russia 23 827 0.7× 185 0.2× 504 0.7× 196 0.3× 411 0.7× 108 1.9k

Countries citing papers authored by X. Sheldon Lin

Since Specialization
Citations

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

Fields of papers citing papers by X. Sheldon Lin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by X. Sheldon Lin. 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 X. Sheldon Lin. The network helps show where X. Sheldon Lin may publish in the future.

Co-authorship network of co-authors of X. Sheldon Lin

This figure shows the co-authorship network connecting the top 25 collaborators of X. Sheldon Lin. A scholar is included among the top collaborators of X. Sheldon Lin 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 X. Sheldon Lin. X. Sheldon Lin 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.
Zhao, Minyang, et al.. (2025). Tea in color: Single-probe nanozyme array for multichannel visual fingerprinting and portable quality evaluation. Journal of Colloid and Interface Science. 703(Pt 2). 139205–139205.
2.
Zhang, Meng, Dapeng Hao, Yancheng Song, et al.. (2025). An interpretable CT-based deep learning model for predicting overall survival in patients with bladder cancer: a multicenter study. npj Precision Oncology. 9(1). 288–288. 2 indexed citations
3.
Wang, Ruichen, et al.. (2024). Compositional Text-to-Image Synthesis with Attention Map Control of Diffusion Models. Proceedings of the AAAI Conference on Artificial Intelligence. 38(6). 5544–5552. 14 indexed citations
4.
Yang, Dong, et al.. (2022). GammaE: Gamma Embeddings for Logical Queries on Knowledge Graphs. 745–760. 6 indexed citations
5.
Gui, Wenyong, et al.. (2018). Fitting the Erlang mixture model to data via a GEM-CMM algorithm. Journal of Computational and Applied Mathematics. 343. 189–205. 22 indexed citations
6.
Lin, X. Sheldon, et al.. (2018). On the consistency of penalized MLEs for Erlang mixtures. Statistics & Probability Letters. 145. 12–20. 4 indexed citations
7.
Lin, X. Sheldon. (2014). Alternating linearization for structured regularization problems. Journal of Machine Learning Research. 15(1). 3447–3481. 10 indexed citations
8.
Chi, Yichun & X. Sheldon Lin. (2012). Are Flexible Premium Variable Annuities Under-Priced?. Astin Bulletin. 42(2). 559–574. 5 indexed citations
9.
Lin, X. Sheldon, Xiangxiang Meng, Prasanna Karunanayaka, & Scott K. Holland. (2011). A Spectral Graphical Model Approach for Learning Brain Connectivity Network of Children's Narrative Comprehension. Brain Connectivity. 1(5). 389–400. 5 indexed citations
10.
Deng, Lei, Shengchang Su, Minlu Zhang, et al.. (2010). Investigating the predictability of essential genes across distantly related organisms using an integrative approach. Nucleic Acids Research. 39(3). 795–807. 109 indexed citations
11.
Zhu, Xingquan, Peng Zhang, X. Sheldon Lin, & Yong Shi. (2010). Active Learning From Stream Data Using Optimal Weight Classifier Ensemble. IEEE Transactions on Systems Man and Cybernetics Part B (Cybernetics). 40(6). 1607–1621. 99 indexed citations
12.
Lin, X. Sheldon, et al.. (2009). Modeling Dependent Risks with Multivariate Erlang Mixtures. Astin Bulletin. 42(1). 153–180. 12 indexed citations
13.
Hong, Huang‐Yao & X. Sheldon Lin. (2008). Introducing people knowledge into science learning. International Conference of Learning Sciences. 366–373. 3 indexed citations
14.
Chen, Yan, Jeff J. Guo, Michael Steinbuch, et al.. (2008). Comparison of sensitivity and timing of early signal detection of four frequently used signal detection methods: An empirical study based on the US FDA adverse event reporting system database. The HKU Scholars Hub (University of Hong Kong). 22(6). 359–365. 11 indexed citations
15.
Lin, X. Sheldon, Jennifer Pittman, & Jennifer Clarke. (2007). Information conversion, effective samples, and parameter size. IEEE Transactions on Information Theory. 53(12). 4438–4456. 9 indexed citations
16.
Gerber, Hans U., X. Sheldon Lin, & Hailiang Yang. (2006). A Note on the Dividends-Penalty Identity and the Optimal Dividend Barrier. Astin Bulletin. 36(2). 489–503. 62 indexed citations
17.
Gerber, Hans U., X. Sheldon Lin, & Hailiang Yang. (2006). A Note on the Dividends-Penalty Identity and the Optimal Dividend Barrier. Astin Bulletin. 36(2). 489–503. 11 indexed citations
18.
Wang, Yan, et al.. (2006). The effect of multiple-perspective thinking on problem solving. International Conference of Learning Sciences. 812–817. 3 indexed citations
19.
Sullivan, Florence R. & X. Sheldon Lin. (2006). The ideal science student and problem solving. International Conference of Learning Sciences. 737–743. 3 indexed citations
20.
Lin, X. Sheldon, Gordon E. Willmot, & Steve Drekic. (2003). The classical risk model with a constant dividend barrier: analysis of the Gerber–Shiu discounted penalty function. Insurance Mathematics and Economics. 33(3). 551–566. 167 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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Ludger Rüschendorf Breakdown of academic impact, for papers by Kai Wang Ng Breakdown of academic impact, for papers by Jean Jacod Breakdown of academic impact, for papers by Minyi Huang Breakdown of academic impact, for papers by Rama Cont Breakdown of academic impact, for papers by Richard L. Dykstra Breakdown of academic impact, for papers by Perwez Shahabuddin Breakdown of academic impact, for papers by Upendra Dave Breakdown of academic impact, for papers by Ken‐iti Sato Breakdown of academic impact, for papers by Sergey Foss
Rankless by CCL
2026