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Research Expertise and Interest

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Name

Department

Peng Ding

Dept of Statistics

Statistical causal inference, missing data, Bayesian statistics, applied statistics

Nikita Zhivotovskiy

Dept of Statistics

mathematical statistics, applied probability, statistical learning theory

Tina Trujillo

School of Education

educational equity, urban schooling, educational leadership, high stakes accountability, school improvement, educational policy, educational management and administration

Michelle Young

School of Education

educational leadership, policy analysis, critical theory, educational equity

Avi Feller

Dept of Statistics

Goldman School of Public Policy

applied statistics, theoretical statistics, Bayesian statistics, machine learning, statistics in social sciences

Deborah Nolan

Dept of Statistics

statistics, empirical process, high-dimensional modeling, technology in education

Woman wearing a red jumpsuit while presenting

Gina Garcia

School of Education

educational equity, educational justice, organizational theory

Sandrine Dudoit

Dept of Statistics

School of Public Health

statistics, machine learning, data science, applied statistics, statistical computing, computational biology, computational genomics, Precision Medicine, precision health

Adityanand Guntuboyina

Dept of Statistics

nonparametric and high-dimensional statistics, shape constrained statistical estimation, empirical processes, statistical information theory

Samuel Lucas

Dept of Sociology

research methods, demography, sociology, social stratification, sociology of education, research statistics

Janelle Scott

School of Education

Dept of African American Studies

educational policy, charter schools, politics of education, race and education, school choice, desegregation, philanthropy and education, advocacy

Dana Miller-Cotto

School of Education

educational equity, early childhood education, cognitive processes, early math learning, social contexts of education

Sophia Rabe-Hesketh

School of Education

biostatistics, educational statistics, latent variable models, missing data methods, multilevel models, generalized linear latent and mixed models, hierarchical models, longitudinal data, Item response models, structural equation models

Will Fithian

Dept of Statistics

Theoretical and Applied Statistics

Michael Jordan

Dept of Statistics

Division of Computer Science (EECS)

computer science, artificial intelligence, computational biology, statistics, machine learning, electrical engineering, applied statistics, optimization

Song Mei

Dept of Statistics

data science, statistics, machine learning

Perry de Valpine

Dept of Environmental Science, Policy & Management

population ecology, mathematical modeling and statistics

Fernando Perez

Dept of Statistics

data science, Educational Data Science, scientific computing

Yun S. Song

Dept of Statistics

Division of Computer Science (EECS)

computational biology, machine learning, applied probability and statistics

Elizabeth Purdom

Dept of Statistics

computational biology, bioinformatics, statistics, data analysis, sequencing, cancer genomics

Uros Seljak

Dept of Physics

astrophysics, cosmology, machine learning, Bayesian statistics

Ahmed Alaa

Computational Precision Health Program

machine learning and artificial intelligence, health care, statistics

Alistair Sinclair

Dept of Statistics

Division of Electrical Engineering (EECS)

algorithms, applied probability, statistics, random walks, Markov chains, computational applications of randomness, Markov chain Monte Carlo, statistical physics, combinatorial optimization

Ryan Giordano

Dept of Statistics

machine learning, variational inference, Bayesian methods, robustness quantification, applied statistics

Amanda Coston

Dept of Statistics

causal inference, machine learning, nonparametric statistics, responsible AI, algorithmic fairness

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