CIMA Lab

The  Statistics Lab for Causal Inference and Missing Data Analysis is led by Dr. Shu Yang. Many important questions in chronic diseases and cancer are about the effects of treatments, e.g., approving drugs, implementing health policies, or identifying optimal personalized treatment strategies. The answers to these questions often rely on complex real-world data suffering from confounding, non-compliance, drop-outs, missing values, etc.

Our research is to develop innovative statistical methods for making accurate inferences about treatment effects from complex observational and clinical studies, including marginal structural models, structural nested models, inverse probability weighting, and matching methods. This research falls into the general area of causal inference and missing data analyses. Our research team applies novel methods in environmental health, cardiovascular diseases, HIV infection, and cancer research to identify effective treatment strategies.

We are always looking for highly motivated students to join CIMA, contact me at syang24(@)ncsu.edu or send an email to [email protected] to subscribe.

CIMA news and activities (here is our website)

CIMA Group Meeting: 2026 Fall

CIMA Group Meeting: 2026 Spring

CIMA Group Meeting: 2025 Fall

CIMA Group Meeting: 2025 Spring

CIMA Group Meeting: 2024 Fall

CIMA Group Meeting: 2024 Spring

CIMA Group Meeting: 2023 Fall

CIMA Group Meeting: 2023 Spring

CIMA Group Meeting: 2022 Fall

CIMA Group Meeting: 2022 Spring

CIMA Group Meeting: 2021 Fall

Resources

Information for CIMA students

Resources for writing and exams

—> Student Award

Student travel or paper award opportunities (managed by Yi Liu)

  1. ASA BIOP Scholarship Award, the ASA Biopharmaceutical Section, Yi Liu, 2026
  2. NSF Travel Award, ICSA 2026 Applied Statistics Symposium, Manting Jin, 2026
  3. NSF Travel Award, ICSA 2026 Applied Statistics Symposium, Anqi Zhao, 2026
  4. NSF Travel Award, ICSA 2026 Applied Statistics Symposium, Siqi Cao, 2026
  5. Honorable Mention of Student Paper Competition, the ASA Biopharmaceutical Section, Sihyung Park, 2026
  6. ENAR Distinguished Paper Competition Award, Eastern North American Region of International Biometric Society Spring Meeting, Sihyung Park, 2026
  7. ENAR Distinguished Paper Competition Award, Eastern North American Region of International Biometric Society Spring Meeting, Xiaodan Zhou, 2026
  8. Merck Research Fellowship Award, North Carolina State University, Sihyung Park, 2026
  9. ARISE 2026–2027 Finalist, ASA Statistics and Data Science in Aging Interest Group, Samhita Pal, 2026
  10. Best Poster Award from the 8th New England Rare Disease Statistics (NERDS) Workshop, Yi Liu, 2025
  11. FDA-OCE-ASA Oncology Educational Fellowship, Ke Zhu, 2025
  12. NISS New Researcher Presentation Award from the NISS Virtual New Researchers Conference, Ke Zhu, 2025
  13. Best Presentation Award from the 38th New England Statistics Symposium, Yi Liu, 2025
  14. Best Student Poster Award from Workshop on Biostatistics & Bioinformatics, Yi Liu, 2025
  15. GSA Conferences and Travel Award, North Carolina State University, Shubhajit Sen, 2025
  16. NSF Graduate Research Fellowship, Anthony Wang, 2025
  17. NeurIPS Scholar Award, Sihyung Park, 2025
  18. ICLR Travel Award, Jianing Chu, 2025
  19. Becton Dickinson Fellowship, North Carolina State University, Manting Jin, 2025
  20. Becton Dickinson Fellowship, North Carolina State University, Yujing Gao, 2025
  21. GlaxoSmithKline Fellowship, Xiaodan Zhou, 2025
  22. NSF Travel Award, 10th Workshop on Biostatistics and Bioinformatics, Ke Zhu, 2025
  23. Finalist, Duke Industry Statistics Symposium Student Paper Competition, Shubhajit Sen, 2025
  24. Gertrude M. Cox Academic Achievement Award, North Carolina State University, Siqi Cao, 2024
  25. Merck Research Fellowship Award, North Carolina State University, Yi Liu, 2025
  26. DISS Best Poster Award from Duke Industry Statistics Symposium, Yi Liu, 2025
  27. IMS Hannan Graduate Student Travel Award from the Institute of Mathematical Statistics, Yi Liu, 2025
  28. GSA Conferences and Travel Award, North Carolina State University, Yi Liu, 2024
  29. Student Paper Competition Award from the LiDA Conference, Chenyin Gao, 2025
  30. Paige Plagge Award for good citizenship from Statistics North Carolina State University to a graduate student with an outstanding academic record and has enhanced the life of fellow students with encouragement, generosity and/or humor, Chenyin Gao, 2024
  31. ICSA Student Paper Award, ICSA Applied Statistics Symposium, Chenyin Gao, 2024
  32. ENAR RAB Student Poster Award Competition, 2nd place, Eastern North American Region of International Biometric Society Spring Meeting, Siyi Liu, 2024
  33. FDA-OCE-ASA Oncology Educational Fellowship, Taekwon Hong, 2024
  34. NHLBI T32 Fellowship, North Carolina State University and Duke Clinical Research Institute, Yi Liu, 2024
  35. MBB Interdisciplinary Mind Grant, Harvard University, Chenyin Gao, 2024
  36. Gertrude M. Cox Achievement Award for the PhD qualifier, North Carolina State University, Manting Jin, 2024
  37. JSM Student Poster Award (honorable mention) from the ASA Biopharmaceutical Section in cooperation with the FDA Statistical Association, Sarah Fairfax, 2023
  38. Student Poster Recognition Award, ASA Biopharmaceutical Section Regulatory-Industry Statistics Workshop, Siyi Liu, 2023
  39. JSM Student Paper Award from the ASA Section on Nonparametric Statistics, Joint Statistical Meetings, Yichi Zhang, 2023
  40. JSM Student and Early-Career Travel Award, Chenyin Gao, 2023
  41. ICML Travel Award, Jianing Chu, 2023
  42. UNC Gillings Merit Award, Anthony Wang, 2023
  43. NIH T32 Environmental Health Sciences Training Grant, University of North Carolina at Chapel Hill, Anthony Wang, 2023
  44. GSA Travel Assistance Award, North Carolina State University, Shubhajit Sen, 2023
  45. AMS Travel Grant, American Mathematical Society, Yunshu Zhang, 2023
  46. First Place, Clint Miller Poster Award, Southern Regional Council on Statistics, Shubhajit Sen, 2022
  47. Boyd Harshbarger Travel Award, Southern Regional Council on Statistics, Shubhajit Sen, 2022
  48. IBM Student Research Award, the 34th New England Statistics Symposium, Lili Wu, 2021
  49. DISS Best Poster Award from Duke Industry Statistics Symposium, Joe Zhao, 2021
  50. JSM Paper Award from the Section on Statistics in Epidemiology, Lili Wu, 2021
  51. ENAR Distinguished Paper Competition Award, Eastern North American Region of International Biometric Society Spring Meeting, Andrew Giffin, 2021
  52. ENAR Distinguished Paper Competition Award, Eastern North American Region of International Biometric Society Spring Meeting, Shuhan Tang, 2021
  53. IMS Hannan Graduate Student Travel Award, Institute of Mathematical Statistics, Yichi Zhang, 2021
  54. ENAR Distinguished Paper Competition Award, Eastern North American Region of International Biometric Society Spring Meeting, Lin Dong, 2020
  55. STATMOS Workshop Travel Award, Andrew Giffin, 2019
  56. ICML Diversity and Inclusion Travel Award, Lili Wu, 2019
  57. SAMSI Graduate Fellow, Precision Medicine Program, Lili Wu, 2018
  58. NIH T32GM081057, Biostatistics Training in the Omics Era, Sarah Fairfax, 2018

—> Current Members

Postdoc fellows

Ph.D. candidates

Master candidates

—> Alumni and Dissertation Involving Causal Inference Research

Previous postdoc fellows

Previous Ph.D. students

Previous Master students

Ph.D. Advisor (2023–2026)
Thesis: Data-adaptive, robustness-preserving, and efficiency-improving methodology for causal effect estimation [link]
Ph.D. Advisor (2021–2026)
Thesis: Semiparametric methods for clinical trial design and inference with external controls and irregular assessments [link]
Master Advisor (2024–2026)
Thesis: Selection bias during enrollment in randomized controlled trials: consequences for generalizability and effective sample size [link]
Ph.D. CO-Advisor with Rui Song (2021–2025)
Thesis: Advanced causal inference for addressing modern challenges: informative sampling, privacy constraints, and point processes [link]
Ph.D. Advisor (2019–2024)
Thesis: Advanced statistical causal inference and individualized treatment regime learning: Data Integration, Inference, and Matching. [link]
Ph.D. Co-Advisor with Wenbin Lu (2019–2024)
Thesis: Advances in Policy Evaluation and Learning: Targeting, Truncation by Death, and One-sided Feedback. [link]
Ph.D. Advisor (2019–2024)
Thesis: Advanced Statistical Methods for Data Integration and Tensor Completion in Causal Inference. [link]
Ph.D. Advisor (2019–2024)
Thesis: Treatment effect evaluation in longitudinal studies with missing data and data integration. [link]
Ph.D. Co-Advisor with Wenbin Lu (2019–2024)

Thesis: Analysis of Irregularly Spaced Longitudinal Market Transaction Data. [link]

Ph.D. Committee Member (2018–2023)

Thesis: Advances in causal inference and the study of interlocus gene conversion [link]

Ph.D. Co-Advisor with Minh Tang (2018–2023)

Thesis: Statistical inference with randomized SVD for signal-plus-noise matrix models and causal inference with continuous interventions [link]

Ph.D. Advisor (2018–2023)

Thesis: Doubly robust estimators of causal effects in observational studies: theory and practice [link]

Ph.D. Co-Advisor with Emily Hector (2018–2023)

Thesis: Advances in Matching Methods for Causal Inference with Multiple Treatments [link]

Ph.D. Advisor (2016–2022)

Thesis: Robust Causal Inference Methods for Using Randomized Clinical Trial and Observational Study [link]

Ph.D. Committee Member (2017–2022)

Thesis: Covariance Function Estimation and Causal Inference Methods [link]

Ph.D. Co-Advisor with Brian Reich (2017–2022)

Thesis: Advances in Semiparametric Quantile Regression [link]

Ph.D. Co-Advisor with Sujit Ghosh (2017–2022)

Thesis: Semiparametric Inference of Randomized Controlled Trials and Observational Studies [link]

Ph.D. Advisor (2016–2021)

Thesis: Spatially Varying and Multi-Source Data Integrative Causal Inference [link]

Ph.D. Committee Member (2017–2021)

Thesis: Advanced Methods in Bayesian Variable Selection and Causal Inference [link]

Ph.D. Committee Member (2017–2021)

Thesis: Online Testing and Semiparametric Estimation of Complex Treatment Effect [link]

Ph.D. Co-Advisor with Marie Davidian (2014–2021)

Thesis: Conducting Causal Inference on Partially Observed Data via Imputation and Matching [link]

Ph.D. Co-Advisor with Brian Reich (2016–2020)

Thesis: Methods for Causal Inference on Spatial Data with Environmental and Public Health Applications [link]

Ph.D. Co-Advisor with Eric Laber (2015–2019)

Thesis: Semiparametric Methods for Decision Making and Causal Effect Generalization [link]

Ph.D. Committee Member (2015–2019)

Thesis: Bayesian Methods for Optimal Treatment Allocation and Causal Inference [link]