Research interests include bounds, policies, and decision making on Probabilities of Causation, monotonicity, and selection bias.

My research interests include social policy evaluation, causal inference methods, early childhood development, family well-being, early adversity prevention, and structural inequality. The aim of my research is to understand how public policies and other structural factors shape early foundations for healthy outcomes over the lifespan.

My research interest lies in causal inference in social science. My substantive research interest includes international political economy and interest group politics.

I am interested in using causal inference methods to better model potential impact of interventions and policies on population health. I am also interested in methods involving simulation for causal inference, including quantitative bias analysis and systems science modeling.

My research interest is in approaches to generalizability and transportability, particularly with applications in medicine, and the teaching of statistics. 

I am broadly interested in causal inference and machine learning methods for the social sciences. My research projects include partial identification of causal quantities and causal inference with survey and voting data.

I'm a Ph.D. student enrolled at Aarhus University in Denmark. In my research I use the Danish National Birth Cohort and the Danish registers to investigate the association between parental socioeconomic factors and reproductive health in children using causal inference methods. 

My primary interests include reproductive epidemiology, causal inference methods, and dermatology. During my PhD, I am researching the relationship between atopic dermatitis and various reproductive health outcomes.

My current research focuses on causal effect estimation and applications of causal methods in public policy settings.

Mixed methods inquiry, academic and labor market experiences of community college students, historically minoritized communities, equity and justice.

I study American Politics and Methodology. My broad research interests are in representation, political behavior, and public policy in state and local governments in the United States, centering on studying the politics of firearm ownership and firearm-based violence and suicide. 

I use machine learning and causal inference tools to study the political economy of U.S. elections. 

My current research interests include developing new models for causal inference and synthetic data generation using tools from transfer metric learning and optimal transport.

I have a master’s degree in health science and a great passion for epidemiological research. Currently, I study how pubertal development affects mental health problems in adolescence.

I study how real-world events interact with voters’ partisan attachments to shape elections and public opinion in the United States. I am broadly interested in electoral accountability, political economy, and political psychology, especially when these topics intersect with public health and gun violence.

Nathan uses the cases of education and sexuality to study how state policies and other national institutions shape social inequality for immigrants. He also engages in methodological research with the aim of educating social scientists in advanced statistical and machine learning methods. 

My current research interests involve causal effects on physiological diseases and the application and effectiveness of treatments on different patient populations. 

My research interest lies in chronic disease epidemiology, with a particular focus on exploring causal association in the presence of incomplete data.

My research interests include adult and child psychiatry, specifically relating to mood disorders, substance use, family dynamics, and unhoused populations.

My research interests include infectious diseases, women’s reproductive health, and occupational health. 

My research is in heterogenous treatment effects, specifically in social settings like education research and policy evaluation. 

The goal of my research is to develop and utilize innovative and rigorous epidemiologic, econometric and causal inference methods, as well as computational modeling and simulation tools for investigating the impact of lifestyle, metabolic and social interventions in preventing chronic diseases.

I am a physician-epidemiologist specializing in the application of various causal inference methods, particularly in the field of chronic disease epidemiology. My recent work focuses on identifying mechanisms (e.g., causal mediation analysis and the front-door formula), detecting heterogeneity (i.e., heterogeneous treatment effect estimation), and generalizing/transporting study results.

I am interested in generalizing results of substance use treatment clinical trials to people with multiple co-occurring mental health disorders.

My research interests are in Development Economics, Labour Economics, and Girls Education, Gender Equality.

My research explores the social and political effects of modern sports. I also work to improve social science methods for causal inference, in particular regression discontinuity analysis and survey designs.

I am interested in target trial emulation from observational data and the application of causal inference to questions about aging physiology.

My key contributions to science are in the field of reproductive epidemiology with a strong focus on the potential effects of prenatal and early life exposures on pubertal development, semen quality, fecundity, fertility and infertility. I have extensive expertise in conducting epidemiologic studies in large birth cohorts and nationwide Danish/Nordic registries by using causal inference methods. 

My research area is reproductive epidemiology with a special focus on early life causes and genetics.

My research interests are primarily in methodological and applied (bio)statistics with a focus on applications of causal inference and machine learning in public and environmental health.

My research interests include developing tools that aid practitioners in making more credible causal inferences, sample selection as a threat to both internal and external validity, placebo methods, and the connections between causal frameworks and across identification strategies.  

I study causal inference in observational and quasi-experimental settings, with a focus on identifying the effects of social inequality on people's life outcomes. 

I am an infectious diseases epidemiologists, with research interests in maternal, perinatal and pediatric vaccine program evaluation. I have considerable experience in the use of linked data to support communicable disease surveillance and control, and in overseeing public health intelligence programs to support policy development and implementation.  

My research is focused on providing timely and practical information about our students, employees, and programs to assist our institutional leadership in making decisions. Recent projects have included evaluating EEO/employee diversity hiring practices, examining the impact of adding a winter term, monitoring campus climate trends, and assessing student progress toward achieving the statewide Vision for Success Goals.

I am a dementia researcher, focused on extending causal inference methods and the target trial framework to study time-varying exposures related to dementia incidence, with a particular interest on selection bias and competing events.