Scholars@Duke

• Background
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  Education, Training, & Certifications

  • Ph.D., Duke University 2012
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  Previous Appointments & Affiliations

  • Assistant Professor of Biostatistics & Bioinformatics, Biostatistics & Bioinformatics, Division of Translational Biomedical, Biostatistics & Bioinformatics 2022
  • Assistant Professor of Biostatistics & Bioinformatics, Biostatistics & Bioinformatics, Basic Science Departments 2022
• Research
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  Selected Grants

  • Quantitative Methods for HIV/AIDS Research awarded by National Institutes of Health 2018 - 2023
  • Immunologic and Virologic Determinants of Congenital Cytomegalovirus Transmission and Disease in Rhesus Monkeys awarded by Weill Cornell Medicine 2020 - 2023
  • Immune Responses to Malaria, HIV and SARS-CoV-2 Infection and Immunization awarded by Seattle Children's Research Institute 2022 - 2023
• Publications & Artistic Works
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  Selected Publications

  • Academic Articles

    • Zhang, Lixiang, Lin Lin, and Jia Li. “Multi-view clustering by CPS-merge analysis with application to multimodal single-cell data.” Plos Comput Biol 19, no. 4 (April 2023): e1011044. https://doi.org/10.1371/journal.pcbi.1011044.
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    • Lin, Lin, Wei Shi, Jianbo Ye, and Jia Li. “Multisource single-cell data integration by MAW barycenter for Gaussian mixture models.” Biometrics, February 27, 2022. https://doi.org/10.1111/biom.13630.
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    • Seo, Beomseok, Lin Lin, and Jia Li. “Block-Wise Variable Selection for Clustering Via Latent States of Mixture Models.” Journal of Computational and Graphical Statistics 31, no. 1 (January 2, 2022): 138–50. https://doi.org/10.1080/10618600.2021.1982724.
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    • Seo, B., L. Lin, and J. Li. “Mixture of Linear Models Co-supervised by Deep Neural Networks.” Journal of Computational and Graphical Statistics 31, no. 4 (January 1, 2022): 1303–17. https://doi.org/10.1080/10618600.2022.2107533.
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    • Zhang, Lixiang, Lin Lin, and Jia Li. “VtNet: A neural network with variable importance assessment.” Stat 10, no. 1 (December 2021). https://doi.org/10.1002/sta4.325.
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    • Lin, L., and B. P. Hejblum. “Bayesian mixture models for cytometry data analysis.” Wiley Interdisciplinary Reviews: Computational Statistics 13, no. 4 (July 1, 2021). https://doi.org/10.1002/wics.1535.
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    • Zarmehri, Sahar, Ephraim M. Hanks, and Lin Lin. “A Sample Covariance-Based Approach For Spatial Binary Data.” Journal of Agricultural, Biological and Environmental Statistics 26, no. 2 (June 2021): 220–49. https://doi.org/10.1007/s13253-020-00424-0.
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    • Chen, Simiao, Qiushi Chen, Juntao Yang, Lin Lin, Linye Li, Lirui Jiao, Pascal Geldsetzer, Chen Wang, Annelies Wilder-Smith, and Till Bärnighausen. “Curbing the COVID-19 pandemic with facility-based isolation of mild cases: a mathematical modeling study.” J Travel Med 28, no. 2 (February 23, 2021). https://doi.org/10.1093/jtm/taaa226.
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    • Li, J., and L. Lin. “Optimal Transport with Relaxed Marginal Constraints.” Ieee Access 9 (January 1, 2021): 58142–60. https://doi.org/10.1109/ACCESS.2021.3072613.
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    • Zhang, Lixiang, Lin Lin, and Jia Li. “CPS analysis: self-contained validation of biomedical data clustering.” Bioinformatics 36, no. 11 (June 1, 2020): 3516–21. https://doi.org/10.1093/bioinformatics/btaa165.
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    • Li, Jia, Beomseok Seo, and Lin Lin. “Optimal transport, mean partition, and uncertainty assessment in cluster analysis.” Statistical Analysis and Data Mining: The Asa Data Science Journal 12, no. 5 (October 2019): 359–77. https://doi.org/10.1002/sam.11418.
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    • Li, Weiling, Lin Lin, Raunaq Malhotra, Lei Yang, Raj Acharya, and Mary Poss. “A computational framework to assess genome-wide distribution of polymorphic human endogenous retrovirus-K In human populations.” Plos Comput Biol 15, no. 3 (March 2019): e1006564. https://doi.org/10.1371/journal.pcbi.1006564.
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    • Lin, L., and D. K. H. Fong. “Bayesian multidimensional scaling procedure with variable selection.” Computational Statistics and Data Analysis 129 (January 1, 2019): 1–13. https://doi.org/10.1016/j.csda.2018.07.007.
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    • Li, Jia, and Lin Lin. “Baum-Welch algorithm on directed acyclic graph for mixtures with latent Bayesian networks.” Stat 6, no. 1 (2017): 303–14. https://doi.org/10.1002/sta4.158.
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    • Lin, Lin, Cliburn Chan, and Mike West. “Discriminative variable subsets in Bayesian classification with mixture models, with application in flow cytometry studies.” Biostatistics 17, no. 1 (January 2016): 40–53. https://doi.org/10.1093/biostatistics/kxv021.
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    • Seshadri, Chetan, Lin Lin, Thomas J. Scriba, Glenna Peterson, David Freidrich, Nicole Frahm, Stephen C. DeRosa, et al. “T Cell Responses against Mycobacterial Lipids and Proteins Are Poorly Correlated in South African Adolescents.” J Immunol 195, no. 10 (November 15, 2015): 4595–4603. https://doi.org/10.4049/jimmunol.1501285.
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    • Lin, Lin, Jacob Frelinger, Wenxin Jiang, Greg Finak, Chetan Seshadri, Pierre-Alexandre Bart, Giuseppe Pantaleo, Julie McElrath, Steve DeRosa, and Raphael Gottardo. “Identification and visualization of multidimensional antigen-specific T-cell populations in polychromatic cytometry data.” Cytometry A 87, no. 7 (July 2015): 675–82. https://doi.org/10.1002/cyto.a.22623.
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    • Lin, Lin, Greg Finak, Kevin Ushey, Chetan Seshadri, Thomas R. Hawn, Nicole Frahm, Thomas J. Scriba, et al. “COMPASS identifies T-cell subsets correlated with clinical outcomes.” Nat Biotechnol 33, no. 6 (June 2015): 610–16. https://doi.org/10.1038/nbt.3187.
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    • Lin, Lin, Cliburn Chan, Sine R. Hadrup, Thomas M. Froesig, Quanli Wang, and Mike West. “Hierarchical Bayesian mixture modelling for antigen-specific T-cell subtyping in combinatorially encoded flow cytometry studies.” Stat Appl Genet Mol Biol 12, no. 3 (June 2013): 309–31. https://doi.org/10.1515/sagmb-2012-0001.
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    • Cron, Andrew, Cécile Gouttefangeas, Jacob Frelinger, Lin Lin, Satwinder K. Singh, Cedrik M. Britten, Marij J. P. Welters, Sjoerd H. van der Burg, Mike West, and Cliburn Chan. “Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples.” Plos Comput Biol 9, no. 7 (2013): e1003130. https://doi.org/10.1371/journal.pcbi.1003130.
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    • Chan, Cliburn, Lin Lin, Jacob Frelinger, Valérie Hérbert, Dominic Gagnon, Claire Landry, Rafick-Pierre Sékaly, et al. “Optimization of a highly standardized carboxyfluorescein succinimidyl ester flow cytometry panel and gating strategy design using discriminative information measure evaluation.” Cytometry A 77, no. 12 (December 2010): 1126–36. https://doi.org/10.1002/cyto.a.20987.
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  • Book Sections

    • Gan, Fah F., Lin Lin, and Chok K. Loke. “Risk-Adjusted Cumulative Sum Charting Procedures.” In Frontiers in Statistical Quality Control 10, 207–25. Physica-Verlag HD, 2012. https://doi.org/10.1007/978-3-7908-2846-7_15.
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  • Conference Papers

    • Guo, Wenbo, Qinglong Wang, Kaixuan Zhang, Alexander G. Ororbia, Sui Huang, Xue Liu, C Lee Giles, Lin Lin, and Xinyu Xing. “Defending Against Adversarial Samples Without Security through Obscurity.” In 2018 Ieee International Conference on Data Mining (Icdm). IEEE, 2018. https://doi.org/10.1109/icdm.2018.00029.
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    • Guan, Le, Jun Xu, Shuai Wang, Xinyu Xing, Lin Lin, Heqing Huang, Peng Liu, and Wenke Lee. “From Physical to Cyber.” In Proceedings of the 14th Acm Conference on Embedded Network Sensor Systems Cd Rom. ACM, 2016. https://doi.org/10.1145/2994551.2994573.
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  • Preprints

    • Li, Weiling, Lin Lin, Raunaq Malhotra, Lei Yang, Raj Acharya, and Mary Poss. “A computational framework to assess genome-wide distribution of polymorphic human endogenous retrovirus-K in human populations.” Cold Spring Harbor Laboratory, October 15, 2018. https://doi.org/10.1101/444034.
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