Professor Yazhen Wang has concluded the final academic year of a transformative three-year term as chair of the Department of Statistics. Under his leadership, the department dramatically increased the size of its student body and faculty, and it added popular new programs at both the undergraduate and graduate levels.
As Wang’s term as department chair winds down, he has officially been selected as the inaugural recipient of the George Box Distinguished Chair in Statistics. This honor makes him the first endowed chair in the department’s history.
The endowed chair is named for the legendary professor and founder of the UW–Madison Department of Statistics, the late George Box, who founded the department in 1960 and served on its faculty until 1992. Wang will hold the George Box Distinguished Chair, funded by the generosity of donors John and Tashia Morgridge, for a period of two years. Wang said the funding will enable him to accelerate leading-edge interdisciplinary research in the fields of quantum computing and data science.
As he shifts his focus from departmental leadership to pioneering research, Wang reflected on how the department has grown under his leadership, what receiving the George Box Distinguished Chair means to him, and how he sees Box’s philosophy of interdisciplinary collaboration guiding the Department of Statistics today and into the future.
A department transformed
Having served as department chair from 2015 through 2018, followed by a sabbatical, Wang re-assumed the role of chair in 2021. His second stint also began soon after the department launched the Data Science undergraduate major, which rapidly blossomed into the fastest-growing program on the UW–Madison campus. Then, in 2022, under Wang’s leadership, the department co-led the creation of the MS Data Science, a joint program with the Department of Computer Sciences (CS). Wang said the Data Science programs marked a turning point for the department in more ways than one.
“In terms of faculty size, we have grown from about 18 faculty members when I started my first term as department chair to 35 today, including our new incoming faculty,” he said. In addition, the Data Science undergraduate major has continued its explosive growth since its founding in fall 2020; today, it has over 1,600 declared majors and has become one of the largest majors on campus.
The MS Data Science, meanwhile, has also attracted talented graduate students from diverse backgrounds. The process of launching the MS program, Wang said, was a prime example of the department’s faculty and staff collaborating effectively with other departments to pursue a common goal. “When we developed the MS Data Science, I was impressed by how well our faculty and staff worked together with CS faculty and staff,” he said. “This program is really a 50-50 split between two equal partners.”
These transformative changes were not without their challenges, Wang said, especially during the pandemic. However, he said, “When I look back, I see that the department is now in a much better position than it was before.”
Another key factor in the department’s growth, Wang said, was joining the School of Computer, Data & Information Sciences (CDIS) in 2019 as one of three founding departments. Wang expressed appreciation to College of Letters & Science (L&S) and CDIS leadership—including L&S Dean Eric Wilcots, as well as CDIS Founding Director Director Tom Erickson, CDIS Associate Director Kristin Eschenfelder and CDIS Director of Advancement Shannon Timm—for steadfastly supporting the department during his time as chair. He said they were especially impactful in connecting faculty and staff members from Statistics with those in other departments, such as CS.
“Everyone, from L&S and CDIS leadership to faculty and staff in Statistics and our fellow CDIS departments, helped us get to the point where we are today,” Wang said. Now, Wang’s focus will shift to frontier research solving statistical puzzles in the field of quantum computing.
A quantum leap forward
The George Box Distinguished Chair, Wang said, will enable him to “speed up” research in quantum computing and data science. Quantum computing is perhaps best explained by drawing a contrast to classical computing, Wang said. “Classical computers are based on classical physics,” Wang noted, “and information is stored using binary bits.” This kind of computing is limited in terms of the speed it can achieve to solve certain tough problems. Today, all modern computers rely on classical physics, including the predictable functioning of electronic circuits in computer chips, Wang added.
Quantum computing, though, relies on the principles of quantum physics, which operate on tiny particles, are unmoored from the principles of classical physics, and are rife with quantumness and randomness and thus extremely difficult to manipulate. That’s where Wang’s statistical expertise comes in. Statistics, after all, is heavily focused on quantifying uncertainty and accounting for randomness and chance. “We need to use statistics to help demonstrate the computational power and certify or refute the work in this field,” Wang said.
In theory, quantum computing could help solve certain hard problems faster than traditional computers. Consider that last year, a Time magazine cover story called quantum computing “the future” and said it could one day “solve problems in seconds that used to take years.” But in practice, Wang said, “there is not yet an available large-scale quantum computer. Our theory says yes, this can be done, but until we can have a practical quantum device that performs tasks faster than a traditional computer, it is just theory.”
Moving from theory to practice, Wang said, will require interdisciplinary collaboration. So he plans to work with researchers across the UW–Madison campus and beyond in search of new breakthroughs. “There are more people than ever working on these problems, including in physics, chemistry, computer science, engineering and other fields,” Wang said. In particular, he mentioned Assistant Professor Swamit Tannu of the Computer Sciences (CS) department, as well as Assistant Professor Micheline Soley of the Chemistry department, as researchers he looks forward to working alongside in search of quantum discoveries.
The Box philosophy
Wang said he only met George Box in person once, at the department’s 50th anniversary celebration over a decade ago. “I remember having a great chat with him,” Wang said. “We shared a lot of the same views on what the future of the department could look like.”
Box remains best known for his expression, “All models are wrong, but some are useful.” But he was also an early proponent of the idea that statistics should play a key role in supporting other academic fields. “George Box was unlike many other leading statisticians of his time because he wanted to build connections with the other disciplines,” Wang said. “This philosophy has influenced me greatly. It inspires me to do interdisciplinary work.”
As Wang begins his two years as the inaugural Box Chair, a philosophy of inclusive collaboration and cross-disciplinary problem solving will be the backbone of his research and teaching. In this way, the legacy of George Box continues to shape the growth and success of the Department of Statistics.
The department wholeheartedly thanks Professor Yazhen Wang for his years of dedicated service as department chair and congratulates him on the honor of being named the first-ever George Box Distinguished Chair in Statistics.
To learn more about Professor Yazhen Wang’s research, visit his website.
For more information about the Data Science major, visit its webpage.
For more information about our graduate programs, visit this page.