Lab

Principal Investigator

Post-doctoral Fellows

contact me at lv2424@columbia.edu or on twitter @valeritweety if you are interested in joining the lab!

Associate Research Scientists

Arce Domingo-Relloso

Arce completed her doctoral degree in Biostatistics National Center of Epidemiology in Madrid in May 2023. She is interested in developing statistical tools for high dimensional omics and the exposome data to uncover their health effects. She joins in 2023 the Valeri Lab to develop causal mediation analysis approaches to investigate the causal effect of air pollutant and metal mixtures on time-to-event and longitudinal markers of cardiovascular disease and Alzheimer’s disease and related disorders in life course studies with severe attrition and drop-out.

PhD Students

Data Analysts

Master Students

Ziqing Wang, BA                                                                                            

Ziqing is developing an R command for mediation analysis with time-to-event mediator and developing an approach for accommodating time-varying confounding.

Yuchen Zhang, BA

Project: Evaluation of a path-specific approach to mediation analysis for longitudinal mediators in the presence of competing risks.                                              

Zhaoqianyu Xiong, BA

Project: Evaluation of propensity score approaches for environmental mixtures health effect estimation.                                              

Feng Yan, BA

Project: R command for the analysis of time-varying environmental mixture effects using BKMR.                                              

Undergraduate Students

Lucy Cambefort (SIBDS summer program)

Project: Evaluating the health effects of environmental mixtures using BKMR incorporating propensity score for confounding adjustment

Malika Top (SIBDS summer program)

Project: Evaluating the health effects of environmental mixtures using BKMR incorporating propensity score for confounding adjustment

Lab Alumni

Zilan Chai, PhD

Zilan’s dissertation concerned the development of machine learning and causal inference approaches to investigate the health effects of environmental mixtures in a life course perspective. Xiaoxuan has joined Microsoft in summer of 2023.

Junzhe Shao, BA                                                                                            

Junzhe has developed a flexible synthetic control method for non-stationary time series to study the effect of interventions to improve COVID-19 vaccine compliance (presented at NeurIPS). He has also contributed to the development of an R package implementing the missing data imputation approach for mHealth studies that we developed in Cai et al. “State space model multiple imputation for missing data in non-stationary multivariate time series“. He has joined UC Berkeley doctoral program in the Fall of 2023.

Zachary Katz, BA                                                                                            

Zak compared machine learning approaches for environmental mixtures studies developing real-world simulation scenarios in the presence of confounding, multicollinearity and complex dose-response relationships. He has joined Takeda in the Summer of 2023.

Xiaoxuan Cai, PhD

Xiaoxuan completed her doctoral degree in Biostatistics in May 2020 working with Forrest W. Crawford, in the School of Public Health at Yale University. She is interested in developing statistical tools to solve real-world problems in epidemiology and public health. She joined in 2020-2022 the Valeri Lab to develop causal inference and missing data analysis approaches to investigate the effect of social activity and social isolation on functional outcomes of severe mental ill patients in N-of-1 long term mobile health observational studies. Xiaoxuan has joined the Department of Statistics Ohio State University as Assistant Professor in the summer of 2022.

Hanyu Lu, MSc                                                                                            

Hanyu’s practicum project involved the extension of methods for mediation analysis to allow for the modeling of multivariate longitudinal latent variable data with application to a pragmatic trial for schizophrenia treatment.

Aijin Wang, BA                                                                                            

Aijin worked as data analyst in the lab between 2019 and 2021. Aijin has developed an R package bkmr-cma to implement causal mediation analysis in the presence of a high dimensional set of exposures (work presented at ISEE 2020 and manuscript in progress). Furthermore, she has applyed machine learning tools for network science and mobile health to investigate the role of social interactions in the management and treatment of schizophrenia (work presented at SOBP 2021). Aijin joined CVS as data scientist in 2021.

Baoyi Shi, MSc                                                                                            

Baoyi worked with Dr. Valeri during her MSc developing the R package CMAverse (published in Epidemiology in 2021) that includes a suite of functions for reproducible conduct of mediation analyses. Baoyi’s research interest is at the intersection of causal inference and functional data analysis. Baoyi started the PhD program in Biostatistics in the Fall of 2020.

Weijia Fan, MSc                                                                                            

Weijia conducted simulation studies to evaluate the performance of novel multistate modeling approaches for mediation analysis in continuous time (published in Statistical Methods for Medical Research in 2023). Weijia started the DrPH program in Biostatistics in the Fall of 2020.

Jingyu Fu, MSc                                                                                            

Evaluation of the impact of US state level policies of business/retail opening on COVID-19 mortality. [Work in collaboration with Dr. Shing Lee lab at Columbia Biostatistics]

Shen Shuyi, MSc                                                                                            

Shen evaluated matching approaches for confounding adjustment to estimate causal effects in N-of-1 time series data.

Mengyu Zhang, MSc                                                                                            

Mengyu evaluated state space models for the estimation of the average period treatment effect in mobile studies in Psychiatry. Mengyu joins the doctoral program in Biostatistics at UT Health in Fall 2021.

Xinru Wang, MSc                                                                                            

Xinru assessed the predictive performance of state space models in mobile studies in Psychiatry in the presence of missing data not at random (manuscript under review). Xinru joins the doctoral program in Biostatistics at Singapore University in Fall 2021.

Weijia Xiong, MSc 

Weijia’s assessed the predictive performance of Hidden Markov models in mobile studies in Psychiatry in the presence of missing data not at random (manuscript in progress). Weijia joins the doctoral program in Biostatistics at Hong Kong University in Fall 2021.

Xinyao Wu, MSc                                                                                            

Xinyao evaluated the performance of generalized propensity score approaches for multiple continuous exposures arising in environmental epidemiology.

Zixu Wang, MSc                                                                                            

Zixu developed visualization tools and prediction models for mobile data streams for clinical use in psychiatry. Zixu joined Dana Farber Cancer Institute as Statistical Analyst in the summer of 2020. Zixu presented his work at the Society of Biological Psychiatry conference in April 2021.

Siyuan Ding, MSc                                                                                            

Siyuan’s practicum concerned the analysis of multivariate longitudinal latent variable data and its application in a pragmatic trial for schizophrenia treatment.

Chuhan Zhou, MSc                                                                                        

Chuhan’s practicum concerned mediation analysis with survival outcome and mediator with application in health disparities research.

Yiwen Zhu, MSc                                                                                        

Yiwen’s research concerned meta-analysis for mediation analysis to integrate information across schizophrenia clinical trials to improve our understanding of antipsychotics effect on quality of life. This work has been published in Epidemiology. Yiwen started the doctoral program in Epidemiology at the Harvard T.H. Chan School of Public Health in the Fall 2020

Xue Zou, MSc

Xue analyzed data from clinical trials involving schizophrenia patients to investigate the relation between neurological adverse events and efficacy of antipsychotics. Xue has joined the Ph.D. program in Bioinformatics at Duke University. We co-author one published paper.

Andrea Bellavia, Ph.D.                                                                                        

Andrea joined my lab as post-doctoral fellow and we co-author 5 articles. His interests lie at the intersection of survival analysis and causal inference with applications in psychiatry and environmental health. He has joined the TIMI group at Brigham and Women’s Hospital and holds an adjunct assistant professor position appointment at the Department of Environmental Health at Harvard T.H. Chan School of Public Health.

Cathy Yuen Yi Lee, Ph.D.    

Cathy investigated via simulation the effects of model misspecification in the estimation of high dimensional exposure-response functions via propensity score adjustment and weighting.  Cathy accepted an offer to join Google.                                                                 

Leah Comment, Ph.D.                                                                                        

I co-advised Leah jointly with Brent Coull and Corwin Ziegler at the Harvard T.H. Chan School of Public Health. Leah developed Bayesian data fusion approaches for unmeasured confounding. We co-author one article in Biometrics. She directs the department of decision sciences at Foundation Medicine.

Katrina Devick, Ph.D.                                                                                        

I co-advised Katrina jointly with Brent Coull at the Harvard T.H. Chan School of Public Health. Katrina developed machine learning approaches for causal mediation analysis. We co-author one article in Biostatistics and one article in Statistics in Medicine. She works as assistant professor at the Mayo Clinic.