Featured Speakers

Rebecca Nugent, Carnegie Mellon University

Rebecca Nugent is the Stephen E. and Joyce Fienberg Professor of Statistics and Data Science, the associate department head and co-director of undergraduate studies for the Carnegie Mellon Statistics and Data Science Department, and an affiliated faculty member of the Block Center for Technology and Society.

Nugent has won several national and university teaching awards, including the American Statistical Association Waller Award for Innovation in Statistics Education, and serves as one of the co-editors of the Springer Texts in Statistics. She recently served on the National Academy of Sciences study, “Envisioning the Data Science Discipline: The Undergraduate Perspective,” and is the co-chair of the current NAS study, “Improving Defense Acquisition Workforce Capability in Data Use.”

Nugent has worked extensively in clustering and classification methodology, with an emphasis on high-dimensional, big data problems and record linkage applications. Her current research focus is the development and deployment of low-barrier data analysis platforms that allow for adaptive instruction and the study of data science as a science

Jeannette Wing, Columbia University

Jeannette M. Wing is Avanessians Director of the Data Science Institute and professor of computer science at Columbia University. She is also adjunct professor of computer science at Carnegie Mellon, where she twice served as the head of the computer science department.

Wing is known for her work on linearizability, behavioral subtyping, attack graphs, and privacy-compliance checkers. Her 2006 seminal essay, titled “Computational Thinking,” is credited with helping to establish the centrality of computer science to problem-solving in fields where it had not been embraced.

Wing’s general research interests are in trustworthy computing, specification and verification, concurrent and distributed systems, programming languages, and software engineering. Her current interests are in the foundations of security and privacy, with a new focus on trustworthy AI.

Robert Tibshirani, Stanford University

Robert Tibshirani has made important contributions to the statistical analysis of complex data sets, including the lasso—which uses L1 penalization in regression and related problems—generalized additive models, and significance analysis of microarrays (SAM). He also co-authored five widely used books: Generalized Additive Models; An Introduction to the Bootstrap; The Elements of Statistical Learning; An Introduction to Statistical Learning; and Sparsity in Statistics: The Lasso and Its Generalizations.

Tibshirani co-authored the first study that linked cell phone usage with car accidents, a widely cited article that has played a role in the introduction of legislation that restricts the use of phones while driving. He is one of the most widely cited authors in the mathematical sciences field.