Yuan Bian

Incoming Postdoc in Biostatistics

Columbia University

Biography

I am an incoming postdoctoral research scientist in Biostatistics at Columbia University, advised by Professor Yuanjia Wang. Currently, I also serve on the Statistical Society of Canada ’s Student and Recent Graduates Committee. I was very fortunate to be supervised by Professors Grace Y. Yi, Wenqing He, Shelley B. Bull, and Rahim Moineddin during my PhD and Master’s studies. I was also pleased to be a research trainee at the Lunenfeld-Tanenbaum Research Institute, the University of Toronto, and the Fields Institute for Research in Mathematical Sciences.

Interests

Ensemble learning
Incomplete data
Variable selection
Reinforcement learning
Uncertainty quantification
Generative models

Education

PhD in Statistics, 2024
University of Western Ontario
MSc in Biostatistics, Thesis Option, 2020
University of Toronto
HBSc in Mathematical Application in Economics and Finance & Statistics, 2017
University of Toronto

Recent Publications

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Statistical inference and learning with incomplete data

PhD thesis 2024, University of Western Ontario

Yuan Bian

Statistical inference and learning with incomplete data

Boosting learning for interval censored data with regression and classification

2024; To be submitted shortly.

Yuan Bian, Grace Y. Yi, Wenqing He

Empirical investigation of boosting with pseudo-outcome imputation for missing responses

2024; Revision invited.

Yuan Bian, Grace Y. Yi, Wenqing He

Unbiased boosting estimation with data missing not at random

2024; Revision invited.

Yuan Bian, Grace Y. Yi, Wenqing He

Physician effects in critical care: A causal inference approach through propensity weighting with parametric and super learning methods

Journal of Data Science 2024; To appear.

Yuan Bian, Yu Shi, Hui Guo, Grace Y. Yi, Wenqing He

Physician effects in critical care: A causal inference approach through propensity weighting with parametric and super learning methods

A unified framework of analyzing missing data and variable selection using regularized likelihood

Computational Statistics and Data Analysis 2024; 194(6): Article 107919.

Yuan Bian, Grace Y. Yi, Wenqing He

A unified framework of analyzing missing data and variable selection using regularized likelihood

Is 14-days a sensible quarantine length for COVID-19? Examinations of some associated issues with a case study of COVID-19 incubation times

Statistics in Biosciences 2022; 14(1): 175-190.

Yasin Khadem Charvadeh, Grace Y. Yi, Yuan Bian, Wenqing He

Is 14-days a sensible quarantine length for COVID-19? Examinations of some associated issues with a case study of COVID-19 incubation times

Incubation and quarantine times: Is 14 days the right quarantine time?

Featured Article in the Statistical Society of Canada Website 2021; Honorable Mention for the Special COVID-19 Case Study Competition

Yasin Khadem Charvadeh, Yuan Bian, Grace Y. Yi, Wenqing He

Incubation and quarantine times: Is 14 days the right quarantine time?

See all publications

Selected Seminar & Conference Presentations

Boosting learning in the presence of incomplete data

Statistical Society of Canada Annual Meeting, Contributed Talk, Won Bilingualism Abstract Award

Jun 5, 2024 Memorial University of Newfoundland

Boosting learning in the presence of incomplete data

Statistical inference and learning with incomplete data

PhD Public Lecture, Oral Presentation

Apr 3, 2024 University of Western Ontario

A unified framework of analyzing missing data and variable selection using regularized likelihood

Xu Lab Seminar, Invited Talk

Mar 12, 2024 University Health Network & University of Toronto (Hybrid)

A unified framework of analyzing missing data and variable selection using regularized likelihood

Canadian Statistical Sciences Institute Annual Showcase, Contributed Talk

Nov 17, 2023 Virtual

Unbiased boosting estimation with data missing not at random

Waterloo Student Conference in Statistics, Actuarial Science and Finance, Contributed Talk

Oct 28, 2023 University of Waterloo

A unified framework of analyzing missing data and variable selection using regularized likelihood

Canadian Statistical Sciences Institute & National Institute of Statistical Sciences - Health Data Science Workshop, Poster Presentation, Won Student and New Researcher Poster Competition

Aug 3, 2023 University of Waterloo

Does cardio/cerebrovascular disease affect subjective rating of health? A case study of causal inference with artificial intelligence

Artificial Intelligence for Public Health Summer Institute, Oral Presentation, Won Canadian Institutes of Health Research Travel Award

Jul 20, 2023 Fields Institute for Research in Mathematical Sciences

Does cardio/cerebrovascular disease affect subjective rating of health? A case study of causal inference with artificial intelligence

A unified framework of analyzing data with response missingness using regularized likelihood

Statistical Data Science Conference, Contributed Talk

Jun 4, 2023 University of British Columbia

A unified framework of analyzing data with response missingness using regularized likelihood

Graduate Colloquium, Oral Presentation

Feb 16, 2023 University of Western Ontario

Is 14-days a sensible quarantine length for COVID-19? A case study of COVID-19 incubation times

Statistical Society of Canada Annual Meeting, Contributed Talk

May 31, 2022 Virtual due to COVID-19 pandemic

Personalized physician recommendation for critical care using the TreeSHAP method

Statistical Society of Canada Annual Meeting, Poster Presentation

May 31, 2022 Virtual due to COVID-19 pandemic

Personalized physician recommendation for critical care using the TreeSHAP method

Analysis of missing data with regularized likelihood

Statistical Society of Canada Annual Meeting, Contributed Talk, Won Student Grant

Jun 11, 2021 Virtual due to COVID-19 pandemic

See all events

Research Experience

Statistical Consultant

Western Data Science Solutions

Sep 2022 – Present London, Ontario

Graduate Research Trainee

Lunenfeld-Tanenbaum Research Institute, Sinai Health

Sep 2018 – Aug 2020 Toronto, Ontario

Research Topics: Joint Models, Survival Analysis, Longitudinal Analysis, Hypothesis Testing, Power Determination, Sample Size

Biostatistics Practicum Researcher

Institute for Clinical Evaluative Sciences & University of Toronto

Sep 2017 – Apr 2018 Toronto, Ontario

Research Topics: Missing Data, Longitudinal Analysis, Randomized Controlled Trials

Research Assistant

Fields Institute for Research in Mathematical Sciences

Jul 2016 – Aug 2016 Toronto, Ontario

Research Topics: Asymptotic Approximation Model, Partial Differential Equation

Teaching Experience

Graduate Teaching Assistant

University of Western Ontario

Sep 2020 – Apr 2024 London, Ontario

Courses: Data Science Concepts, Introduction to Statistics, Statistics for Science, Probability & Statistics II, Generalized Linear Models, Statistical Modeling I, Statistical Modeling II, Advanced Data Analysis, Time Series, Introduction to Study Design, Statistical Inference

Graduate Teaching Assistant

University of Toronto

Sep 2017 – Dec 2020 Toronto, Ontario

Courses: Calculus I, Calculus II, Multivariate Calculus, Discrete Mathematics, Linear Algebra II, Statistics I, Introduction to Probability, Introduction to Statistics, Probability & Statistics I, Probability & Statistics II, Regression Analysis, Time Series Analysis, Methods of Applied Statistics, Machine Learning and Data Mining

Undergraduate Teaching Assistant

University of Toronto

Sep 2014 – Aug 2017 Toronto, Ontario

Courses: Calculus I, Calculus II, Multivariate Calculus, Discrete Mathematics, Linear Algebra I, Differential Equation, Statistics I, Introduction to Probability, Introduction to Statistics