{"id":848,"date":"2020-12-03T11:21:49","date_gmt":"2020-12-03T16:21:49","guid":{"rendered":"https:\/\/scienceweb.clemson.edu\/chg\/?p=848"},"modified":"2025-07-30T10:17:21","modified_gmt":"2025-07-30T14:17:21","slug":"dr-xinyi-li","status":"publish","type":"post","link":"https:\/\/scienceweb.clemson.edu\/ihg\/dr-xinyi-li\/","title":{"rendered":"Dr. Xinyi Li"},"content":{"rendered":"

[et_pb_section fb_built=”1″ admin_label=”section” _builder_version=”4.16″ global_colors_info=”{}”][et_pb_row admin_label=”row” _builder_version=”4.16″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” global_colors_info=”{}”][et_pb_column type=”4_4″ _builder_version=”4.16″ custom_padding=”|||” global_colors_info=”{}” custom_padding__hover=”|||”][et_pb_text admin_label=”Text” _builder_version=”4.27.4″ background_size=”initial” background_position=”top_left” background_repeat=”repeat” hover_enabled=”0″ global_colors_info=”{}” sticky_enabled=”0″]<\/p>\n

Assistant Professor, School of Mathematical and Statistical Sciences<\/strong><\/p>\n

Email: lixinyi@clemson.edu<\/p>\n

Visit the Li Lab<\/a><\/p>\n

\"20120702<\/p>\n

Biosketch<\/strong><\/h2>\n

I am currently an assistant professor in the School of Mathematical and Statistical Sciences. Before joining Clemson, I was a postdoctoral fellow at the Statistical and Applied Mathematical Sciences Institute (SAMSI) and the University of North Carolina at Chapel Hill. I completed my bachelor’s degree in mathematical statistics from Beijing Normal University (Beijing, China). I then earned a master’s degree in statistics at the University of Georgia, and a Ph.D. in statistics at Iowa State University.<\/p>\n

Research<\/strong><\/h2>\n

My research interests include, but are not limited to, precision medicine, functional data analysis, non-\/semi-parametric high-dimensional regression, spatio-temporal analysis, with application to statistical genetics, neuroimaging and public health.<\/p>\n

Selected Publications<\/strong><\/h2>\n

Li, X.<\/strong>, Yu, S., Wang, Y., Wang, G., Wang, L. and Lai M-J. (2024) Nonparametric regression for 3D point cloud learning. Journal of Machine Learning Research, 25(102), 1\u201356.<\/p>\n

Li, X.<\/strong>, Freeman, N. and Wang, L. Q-Learning Based Methods for Dynamic Treatment Regimes. (2023) In Yichuan Zhao and Dinggen Chen (Eds) Precision Medicine: Methods and Applications, Springer.<\/p>\n

Cramer, E., Ray, E., Lopez, V., [et al, including Li, X.<\/strong>] (2022) Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US. Proceedings of the National Academy of Sciences, 119(15), e2113561119.<\/p>\n

Li, X.<\/strong>, Wang, L. and Wang, H. (2021) Sparse learning and structure identification for ultra- high-dimensional image-on-scalar regression. Journal of the American Statistical Association (Theory and Methods), 116(536), 1994\u20132008.<\/p>\n

Cho, H., Zitkovsky, J., Li, X.<\/strong>, Lu, M., Shah, K., Sperger, J., Tsilimigras M. C. B. and Kosorok, M. R. (2020) Comment: Diagnostics and kernel-based extensions for linear mixed effects models with endogenous covariates. Statistical Science, 35(3), 396-399.<\/p>\n

Li, X.<\/strong>, Wang, L. and Nettleton, D. (2019) Simultaneous sparse model identification and learning for ultra-high-dimensional additive partially linear models. Journal of Multivariate Analysis, 173, 204-228.<\/p>\n

[\/et_pb_text][\/et_pb_column][\/et_pb_row][\/et_pb_section]<\/p>\n","protected":false},"excerpt":{"rendered":"

Assistant Professor, School of Mathematical and Statistical Sciences Email: lixinyi@clemson.edu Visit the Li Lab Biosketch I am currently an assistant professor in the School of Mathematical and Statistical Sciences. Before joining Clemson, I was a postdoctoral fellow at the Statistical and Applied Mathematical Sciences Institute (SAMSI) and the University of North Carolina at Chapel Hill. […]<\/p>\n","protected":false},"author":13,"featured_media":849,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_et_pb_use_builder":"on","_et_pb_old_content":"Assistant Professor, School of Mathematical and Statistical Sciences<\/strong>\r\n\r\nEmail: lixinyi@clemson.edu\r\n\r\nVisit the Li Lab<\/a>\r\n\r\n\"20120702\r\n

Biosketch<\/strong><\/h3>\r\nI am currently an assistant professor in the School of Mathematical and Statistical Sciences. Before joining Clemson, I was a postdoctoral fellow at the Statistical and Applied Mathematical Sciences Institute (SAMSI) and the University of North Carolina at Chapel Hill. I completed my bachelor's degree in mathematical statistics from Beijing Normal University (Beijing, China). I then earned a master's degree in statistics at the University of Georgia, and a Ph.D. in statistics at Iowa State University.\r\n

Research<\/strong><\/h3>\r\nMy research interests include, but are not limited to, precision medicine, functional data analysis, non-\/semi-parametric high-dimensional regression, spatio-temporal analysis, with application to statistical genetics, neuroimaging and public health.\r\n

Selected Publications<\/strong><\/h3>\r\nLi, X.<\/strong>, Yu, S., Wang, Y., Wang, G., Wang, L. and Lai M-J. (2024) Nonparametric regression for 3D point cloud learning. Journal of Machine Learning Research, 25(102), 1\u201356.\r\n\r\nLi, X.<\/strong>, Freeman, N. and Wang, L. Q-Learning Based Methods for Dynamic Treatment Regimes. (2023) In Yichuan Zhao and Dinggen Chen (Eds) Precision Medicine: Methods and Applications, Springer.\r\n\r\nCramer, E., Ray, E., Lopez, V., [et al, including Li, X.<\/strong>] (2022) Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US. Proceedings of the National Academy of Sciences, 119(15), e2113561119.\r\n\r\nLi, X.<\/strong>, Wang, L. and Wang, H. (2021) Sparse learning and structure identification for ultra- high-dimensional image-on-scalar regression. Journal of the American Statistical Association (Theory and Methods), 116(536), 1994\u20132008.\r\n\r\nCho, H., Zitkovsky, J., Li, X.<\/strong>, Lu, M., Shah, K., Sperger, J., Tsilimigras M. C. B. and Kosorok, M. R. (2020) Comment: Diagnostics and kernel-based extensions for linear mixed effects models with endogenous covariates. Statistical Science, 35(3), 396-399.\r\n\r\nLi, X.<\/strong>, Wang, L. and Nettleton, D. (2019) Simultaneous sparse model identification and learning for ultra-high-dimensional additive partially linear models. Journal of Multivariate Analysis, 173, 204-228.","_et_gb_content_width":"","footnotes":"","_links_to":"","_links_to_target":""},"categories":[12],"tags":[],"class_list":["post-848","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-faculty"],"_links":{"self":[{"href":"https:\/\/scienceweb.clemson.edu\/ihg\/wp-json\/wp\/v2\/posts\/848","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/scienceweb.clemson.edu\/ihg\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/scienceweb.clemson.edu\/ihg\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/scienceweb.clemson.edu\/ihg\/wp-json\/wp\/v2\/users\/13"}],"replies":[{"embeddable":true,"href":"https:\/\/scienceweb.clemson.edu\/ihg\/wp-json\/wp\/v2\/comments?post=848"}],"version-history":[{"count":0,"href":"https:\/\/scienceweb.clemson.edu\/ihg\/wp-json\/wp\/v2\/posts\/848\/revisions"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/scienceweb.clemson.edu\/ihg\/wp-json\/wp\/v2\/media\/849"}],"wp:attachment":[{"href":"https:\/\/scienceweb.clemson.edu\/ihg\/wp-json\/wp\/v2\/media?parent=848"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/scienceweb.clemson.edu\/ihg\/wp-json\/wp\/v2\/categories?post=848"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/scienceweb.clemson.edu\/ihg\/wp-json\/wp\/v2\/tags?post=848"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}