Bing Wen Brunton joined the faculty at University of Washington (UW) in 2014 to build an interdisciplinary research program at the intersection of biology, neuroengineering, and data science. She is currently a Professor and H. Stewart Parker Faculty Fellow at the Department of Biology, with affiliations at the eScience Institute for Data Science, the Paul G. Allen School of Computer Science & Engineering, and the Department of Applied Mathematics. She studied at Caltech (2006, B.S. in Biology, focus on biophysics) and then Princeton (2012, Ph.D. in Neuroscience, focus on computational and systems neuroscience). Her postdoctoral work (2012--2014, University of Washington) expanded her expertise in applied mathematics, dynamical systems, and neuroengineering.
Her lab now develops data-driven analytic methods that are applied to, and are inspired by, neuroscience. The Brunton Lab is particularly interested in uncovering spatiotemporal patterns in high-dimensional, time-series data, especially exploring the neural basis of naturalistic movements in diverse animals. She has demonstrated a strong record of working collaboratively as a part of interdisciplinary teams, as well as mentoring early career researchers interested in advancing both methods development and neuroscience questions. Her work has been recognized with awards and honors, including the Alfred P. Sloan Foundation Fellowship in Neuroscience (2016), a UW Innovation Award (2017), a Young Investigator Program award from the Air Force Office of Scientific Research (2018), and as a Weill Neurohub Investigator (2020) and a Moore Distinguished Scholar for visiting faculty at Caltech (2021).
Beyond the Briefing
As is so often the case, the official academic biography leaves unsaid most of what really happened. I'd like to share a bit more about myself and how I got here, in the hope that it is of some interest to others who are on their own unique life and career trajectories.
I was born in China and immigrated to the US with my family when I was 10. My parents are both physicists by training and eventually worked as scientists at NASA before they retired. I attended pubic schools in Maryland, including the Science, Math & Computer Science Magnet Program at Montgomery Blair High School. For two summers, I had the privilege of doing research at the NIH, where I gained some experience in molecular histology techniques and also learned that I am drawn towards the quantitative aspects of biology. Math, physics, and computer science have always been core parts of how I like to approach biological questions.
As an undergrad at Caltech, I majored in Biology, which ended up being an excellent excuse for me to dive deeper into physics and quantitative biology. I had a great time, got in some mischief, and spent long evenings doing open-ended problem sets with friends. To this day, I routinely pretend that hard problems in research are just homework problems. Over several summers, I did both experimental and computational research on the structure of microbial cells in Grant Jensen's lab. Steve Brunton and I met at Caltech early on as undergrads. We’ve been migrating together as an acaduo ever since and he has a story that parallels mine, but you’ll have to ask him about it.
My first experience in teaching came from being a TA for Henry Lester's captivating class on Drugs & the Brain. From Henry, I learned not only how to get undergrads interested in biology (e.g. talk about drugs) but also how an instructor invests in training TAs in pedagogy. A few more courses that were formative in how I approach teaching and science were Rob Phillip's and Christof Koch's classes on Biophysics and on Visual Consciousness. After taking Dynamical Systems taught by Jerry Marsden, I realized that these are the methods I want to use to understand biology --- living systems are, after all, fundamentally defined by their spectacular ability to change in time.
When I started thinking about what to do after undergrad, I wasn't sure if I wanted to pursue a Ph.D. Until then, I hadn't seriously considered other options, and I didn't want to simply follow the path for lack of creativity. So, Grant gave me some sage advice that I still think about on a regular basis. When deciding what to work on, he told me that there are three criteria that people should look for: what you're good at, what you like to do, and what's important for the world. He then said that most people are good with two out of three, but if I find something that fits all three, I should not hesitate and go for it. This bit of wisdom has guided my decision-making process many times. Especially when faced with walking into a position with substantial uncertainty, I try to choose options where I'll be challenged, where I'll learn something valuable, and where I might make a difference while spending time with fun people.
As a grad student at Princeton, after attending a talk by Carlos Brody mostly because there was free pizza, I joined the Brody lab. I had to catch up on some neurobiology, but I loved the combination of systems neuroscience experiments and dynamical systems theory. Carlos was a wonderful mentor for me; he gave me plenty of space to explore (i.e. to make mistakes), never failed to make time to help when I asked, and always supported my long-term goals. I also learned a ton from the postdocs who built the experiments in the lab and the other graduate students in the department. I was very fortunate to have learned from several other faculty at Princeton, especially David Tank, Yael Niv, Bill Bialek, and Matt Botvinick. The bulk of my graduate work ended up being computational modeling, but I had lots of fun also building behavioral rigs, assembling electrodes, and performing surgeries along the way.
Steve and I next returned to the west coast to the University of Washington in Seattle. Among our many collaborations, we added two epsilons: our first kid was born during grad school, and our second kid during the first year of postdoc. I am grateful for the grace and patience of my postdoc advisors Tom Daniel and Nathan Kutz, who guided my work through these transitions, including the shift to doing primarily computational research. I still get to work with both of them, and seeing how they approach advising---especially diverse advising challenges---has taught me a lot as I strive to be a good mentor. It is with remarkable good fortune that Steve and I were both hired as faculty at the University of Washington; I was promoted with tenure in 2019.
My philosophy in research has been simple: I follow interesting ideas and work with fun people I enjoy talking science with. I particularly like talking about brains, natural behaviors, and modeling high-dimensional time-series data. New research directions have come from colleagues with a cool dataset, students who arrive with a quirky idea, and hallway conversations that get lodged in my mind. This is perhaps not the most purposeful way to go through an academic career, but I think it is one way to keep having fun and growing. I am privileged to have had the freedom and support to be driven by my curiosity, and I still find it incredible that I get paid to write about research, advise talented early career researchers, teach topics I want to share with undergrads, and use my voice so that others may have the opportunities they want in their lives and careers.