Mengbing Li

PhD Candidate (Biostat)

University of Michigan
Website
Google Scholar
Email
mengbingobfuscate@umich[punto]edu

Education:

2017-19, M.S. in Biostatistics, University of Michigan, Ann Arbor

2013-17, B.S.P.H., Biostatistics and Mathematics. Minor: Statistics, University of North Carolina at Chapel Hill. Graduated with Highest Honor and Distinction

Awards:

  • 2024, Excellence in Research, Honorable Mention, Department of Biostatistics, UMich
  • 2024, MICDE Fellowship (Michigan Institute for Computational Discovery & Engineering)
  • 2023, ENAR Distinguished Student Paper Award, Baltimore 2024
  • 2023, Outstanding Graduate Student Instructor (Biostatistics)
  • 2023, Institute of Mathematical Statistics Hannan Graduate Student Travel Award
  • 2023, Winner of Research Poster Competition, International Biometric Society, Eastern North American Region, Nashville, TN
  • 2019, Best Doctoral Qualifying Exam Award
  • 2018, Outstanding Graduate Student Instructor (Biostatistics)
Papers (partial)

1. ddtlcm: An R package for overcoming weak separation in Bayesian latent class analysis via tree-regularization. Mengbing Li, Bolin Wu, Briana Stephenson, Zhenke Wu (2024) ► JOSS. [paper link] [code] [doi] [pdf]

2. Tree-informed Bayesian multi-source domain adaptation: cross-population probabilistic cause-of-death assignment using verbal autopsy. Zhenke Wu, Zehang Li, Irena Chen, Mengbing Li (2023) ► Biostatistics. [paper link] [code] [supplement] [slides]

3. Tree-Regularized Bayesian Latent Class Analysis for Improving Weakly Separated Dietary Pattern Subtyping in Small-Sized Subpopulations. Mengbing Li, Briana Stephenson, Zhenke Wu (submitted) ► [paper link] [code]

4. Using source-associated mobile genetic elements to identify zoonotic extraintestinal E. coli infections. Cindy Liu, Maliha Aziz, Daniel Park, Zhenke Wu, Marc Stegger, Mengbing Li, Yashan Wang, Kara Schmidlin, Timothy Johnson, Benjamin Koch, Bruce Hungate, Lora Nordstrom, Lori Gauld, Brett Weaver, Diana Rolland, Sally Statham, Brantley Hall, Sanjeev Sariya, Gregg Davis, Paul Keim, James Johnson, Lance Price (2023) ► One Health. [paper link] [doi]

5. Doubly Inhomogeneous Reinforcement Learning. Liyuan Hu*, Mengbing Li*, Chengchun Shi, Zhenke Wu, Piotr Fryzlewicz (submitted) ► [paper link] [code]

6. Reinforcement Learning in Possibly Nonstationary Environment. Mengbing Li, Chengchun Shi, Zhenke Wu, Piotr Fryzlewicz (submitted) ► [paper link] [code] [pdf] [supplement]

7. Factors associated with inferior vena cava placement and retrieval for patients with cancer associated thrombosis. Subhash Edupuganti, Mengbing Li, Zhenke Wu, Tanima Basu, Geoffrey Barnes, Marc Carrier, Suman Sood, Jennifer Griggs, Jordan Schaefer (2021) ► The American Journal of Medicine. [paper link] [doi]

8. Integrating Sample Similarities into Latent Class Analysis: A Tree-Structured Shrinkage Approach. Mengbing Li, Daniel Park, Maliha Aziz, Cindy M Liu, Lance Price, Zhenke Wu (2021) ► Biometrics. In press. [paper link] [code] [pdf] [supplement]

9. Clinical and Sociodemographic Factors Associated with Anticoagulant Use for Cancer Associated Thrombosis.. Jordan Schaefer, Mengbing Li, Zhenke Wu, Tanima Basu, Geoffrey Barnes, Marc Carrier, Jennifer Griggs, Suman Sood (2020) ► Journal of Thrombosis and Thrombolysis [paper link] [doi]

10. Anticoagulant Medication Adherence for Cancer Associated Thrombosis: A Comparison of LMWH to DOACs. Jordan K. Schaefer, Mengbing Li, Zhenke Wu, Tanima Basu, Michael P. Dorsch, PharmD, Geoffrey D. Barnes, Marc Carrier, Jennifer J. Griggs, Suman L. Sood (2020) ► Journal of Thrombosis and Haemostasis [paper link] [doi]