The 21st Century has seen statistical data science flourish as a field and emerge as an important area of scientific endeavor and scholarship. This is largely driven by a number of factors, including greatly increased computing power, an unprecedented capability for data collection and the development of statistical and machine learning methods to analyze and gain insights from modern massive data. Furthermore, statistics as a field has expanded to include not only the traditional subjects of mathematical statistics, methodological statistics, applied statistics and biostatistics but also several modern frontiers, in which statistics interacts with other disciplines, such as computer science and engineering. Such modern areas of data science are not confined to statistics, especially in the view of professionals engaging in the data science domain. Yet, these areas are nevertheless closely related to statistical ideas, use statistical methods of some form or another, and, more importantly, are starting to shape the future of modern statistics.
This modern trend not only has made significant impact in research directions; it also has led to a broad change in education. Virtually no academic department has been left untouched by these trends, and the formerly Department of Statistics (DS), now Department of Statistics and Data Science (DSDS), at UC Davis is no exception. For example, in recent years the Department has added new Data Science and Machine Learning tracks in our undergraduate program. In fact, DSDS is the home to the interdisciplinary Data Science major. The program brings together Statistics, Computer Science, and Mathematics with fields of applications, giving students the strong foundational training underlying modern data analysis. Alongside technical training, students learn to address complex questions with data, communicate their findings clearly, and consider the ethical implications of their work. The major reflects our department’s commitment to preparing students for successful careers in academia and industry.
These changes have powered a significant increase in the number of undergraduate students in the Statistics Major, which is currently ranked #3 in the U.S. according to the U.S. News in terms of the undergraduate degrees awarded. Such a significant increase is largely driven by the prospect of data-science related jobs. In terms of graduate education, based on our experience from the recruitment of tenure-track assistant professors in recent years, there has been consistently a strong pool of candidates, including fresh Ph.D. graduates and postdoctoral researchers, from Statistics, Computer Science, Mathematics, Engineering, and other fields.
The combination of statistics and data science has become so popular these days that some major statistics departments in the U.S., and around the world, have made changes in their names to incorporate this modern trend. The recently approved name-change for the Department, from DS to DSDS, is a step forward following this national and international trend.
While Data Science is now a much bigger field than what Statistics used to be, there are characteristics of Statistical Data Science that distinguishes itself from other disciplines. These include uncertainty quantification, sampling techniques, Monte-Carlo methods, and optimality in inference. These characteristics are increasingly being adopted, and made more computationally effective as well as more practical, by other disciplines of Data Science. On the other hand, ideas, concepts, and techniques from all fields, including Computer Science, Economics, Engineering, Mathematics and Statistics, are shaping the modern Data Science. We need to ride this tide and take advantage of this golden opportunity.
This is a time when opportunities and challenges coexist. Among the main challenges is artificial intelligence (AI). Specifically, we need to take advantage of the AI in assisting student learning without letting it to jeopardize the fair evaluation of the learning performance. There are also major challenges within the UC system, or on the UC Davis campus, many of which are financially related. Like the formerly DS, DSDS will stand tall to these challenges and continue to grow.
While our name has changed, from DS to DSDS, or DS^2, our mission has not. We will maintain the excellence of our programs. For example, according to the latest U.S. News, our Statistics Graduate Program is currently ranked #12 in the nation (tied with UCLA). We will sustain healthy growth in our students and faculty. Our programs will keep getting better. In mathematics, from x to x^2 is a big increase (assuming that x>1). This is how we view the future of our Department, and the future of Statistics and Data Science.
We warmly welcome you to explore our Department’s website under the new name of Statistics and Data Science. More importantly, we encourage you to explore every aspect of our Department, and join us as we explore the new frontiers of Statistics and Data Science.
Professor Jiming Jiang
Chair, Department of Statistics and Data Science
September, 2026