Finding a Research Advisor / Forming a Doctoral or Masters Committee
Students are encouraged to begin thinking about their research interests as early as possible and to seek out faculty members who might serve on their doctoral committee (Ph.D.) or thesis committee (M.S., MAS). Doctoral students are expected to have chosen a Faculty Adviser by the Fall of their second year and discuss with their faculty adviser who will be on their committee over the next quarters. After forming the committee, they should complete their University Oral Qualifying Examination by the end of their second year. Masters students should choose their Faculty Adviser and discuss with their faculty adviser who will be on your committee by the Fall of their second year.
To help with the selection of the Faculty Advisor (i.e., the Chair of their committee), the videos below give a brief introduction to the research areas and styles of the faculty. The same information and discussion with their Faculty Advisor will help with choosing the other committee members. Faculty love to talk about research and encourage students to approach them with questions such as: “What should I read to find out more about the areas you work in?”.
Arash Ali Amini, Associate Professor
High-dimensional inference, machine learning, optimization, networks
Guang Cheng, Professor
Trustworthy AI, Data-Centric AI, Deep Learning Theory and Statistical Machine Learning
Xiaowu Dai, Assistant Professor
Machine learning and economics, Statistical inference in dynamic systems, High-dimensional statistics, and Causal inference.
Alyson (Allie) Fletcher, Associate Professor
Machine learning, Statistical inference for high-dimensional data with applications in neuroscience, signal processing, information theory
Tao Gao, Assistant Professor of Communications
Cognitive Modeling, Human-Machine Teaming, Multi-Agent System
Robert Gould, Senior Lecturer SOE and Undergraduate Vice Chair
Statistics education and Modeling longitudinal data
Mark S. Handcock, Professor and Graduate Vice Chair
Stochastic modeling of social networks, Environmental and spatial statistics, Demography, Computational statistics, Survey sampling, and Epidemiology.
Chad Hazlett, Associate Professor
Causal inference, high-dimensional regression and classification, applications in political science
Jingyi Jessica Li, Professor
Applied Statistics and Statistical Modeling, as well as their interface with Statistical Genomics, Bioinformatics, and Computational Biology
Ker-Chau Li, Distinguished Professor
Dimension reduction, data visualization, time series, images, and gene expression
Oscar Madrid Padilla, Assistant Professor
High dimensional statistics, Network estimation problems, Change point detection, Bayesian statistics, Quantile regression, and Graphical models.
Karen McKinnon, Assistant Professor
Spatial and environmental statistics, predictive modeling, applications to climate science
George Michailidis, Professor
Analysis of high dimensional data, machine learning, network analytics, bioinformatics, visualization
Guido Montufar, Associate Professor
Deep learning, artificial neural networks, information geometry, algebraic statistics
Rick Schoenberg, Professor and Director of MAS Program
Point processes, Image analysis, Time series, and applications especially in seismology and fire ecology
Qing Zhou, Professor
Computational biology, Statistical learning, Monte Carlo methods, Energy landscapes
There is information on more faculty in the faculty directory page.
Note to MAS students: Any faculty listed could be your faculty advisor whether or not they will serve on the official committee or not. Please contact the MAS Advisor for other questions.