REU Site: Research for Undergraduates Summer Institute of Statistics at Oregon State University -- RUSIS@OSU

The Research for Undergraduates Summer Institute of Statistics at Oregon State University (RUSIS@OSU) is the continuation of a successful (AMS award-winning) summer REU site. The underlying motivation for the Institute is to attract more students into graduate work in the Mathematical and Statistical Sciences, and facilitate their transition into research work at a time when demand for human resources with data analytic skills easily exceeds the supply.

RUSIS @OSU will recruit selected underrepresented minority students and students with no easy access to a research experience at their institutions, including students from Community Colleges, Tribal Colleges, Historically Black Colleges (HBCUs) and Hispanic Serving Institutions (HSIs), with the specific goal of mentoring and training them for careers in research in the mathematical sciences and more specifically in Statistics. RUSIS@OSU will prepare students to compete globally in a vibrant world where data-driven decisions are becoming more prominent in all human endeavors.

While the program has been successful in motivating and enticing students to pursue graduate careers in the statistical sciences, it also provides the necessary tools for students to join the workforce in a wide range of professional positions. From academic jobs, to jobs in the pharmaceutical companies, private industry, government agencies and national laboratories, professional sports as data analysts, and climate scientists, the job outlook for statisticians and data scientists is excellent.

The goals of the summer at RUSIS@OSU are accomplished through the following mechanisms: (1) an intensive short course in probability and statistics and an intensive seminar in computation. In addition, topics in stochastic processes, and statistical inference, with special emphasis on areas of current interest will be discussed; (2) engaging the students in research projects from areas of current interest.

Statistical thinking is ubiquitous in every aspect of modern life. Data Mining, Big Data, Data Analytics, Knowledge Discovery are terms that have been coined in the past to denote essentially the same thing: activities related to the extraction of information from data to advance science, technology, and society. Through mentoring and supervision by faculty, the students develop skills that will help them during graduate school and their graduate research stages; (3) the students, motivated by current interest in the development of new methodologies to respond to needs in high dimensional data analyses, will engage in research projects that will be selected from areas of current applied and theoretical interest (e.g. multiple comparisons, dimension reduction, random matrices, extreme value theory, multivariate survival analysis, statistical genetics, massive data methodologies, and modeling of the power grid and other complex urban infrastructures).

Autonomous systems (e.g. autonomous cars) that make use of statistical techniques such as pattern recognition, statistical learning, and dimension reduction methodologies provide interesting problems; (4) students will present their results at national meetings and they will be mentored in the preparation and presentation of their talks. Short courses in LaTeX, and software used for research purposes (Mathematica, MatLab, R) will be taught; (5) visits to scientific facilities (e.g., Linus Pauling Institute @ OSU) will be organized; (6) the progress of students for seven years (expected time for them to finish graduate school) after their participation will be monitored and annual evaluation of the program by the participating students and an external advisory committee will take place.

More details about the REU Site are avaialble at https://stat.oregonstate.edu/rusis@OSU

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.