Name: Mariel Pettee
Title, including department and school you work in: Assistant Professor of Physics and Bernice Durand Faculty Fellow
Hometown: Dallas, TX
Educational/professional background: AB in Physics & Mathematics from Harvard University (2014), MASt in Physics from the University of Cambridge, Trinity College (2015), PhD in Physics from Yale University (2021). I then spent four years as a Chamberlain Postdoctoral Fellow at Lawrence Berkeley National Laboratory, with a joint affiliation as a Guest Researcher at the Flatiron Institute in New York City.
What is your field of research, and how did you get into it? I am a particle physicist by training, but my research these days is more of an interdisciplinary mix of fields viewed through the lens of data science. My work explores the interplay between AI & the physical sciences (primarily particle physics and astrophysics). I’m curious about what physicists will learn when we can perform analyses that integrate diverse sources of data from across various input sources, experiments, and scales.
What attracted you to UW–Madison? Because my research interests are pretty varied, I was hoping to find a position that celebrated, not just tolerated, interdisciplinary physics research grounded in AI methods. My role at UW–Madison as a RISE AI faculty member is precisely that, and that feels quite rare and special. Moreover, the culture in the department, school, and the city of Madison as a whole feels like a great fit.
What was your first visit to campus like? It was snowing! The faculty, staff, and students I spoke with struck me as brilliant, curious, down-to-earth, and kind.
What’s the most important lesson you wish to convey to students? Learning new things is one of life’s biggest joys, one that hopefully you will keep with you throughout your whole life. This is only possible long-term if you find a way to make it sustainable and not burn out. Try to accept the stress and insecurities that come up in the learning process — those never really go away — and see if you can use your time as a student to figure out how to simply love the practice of starting from scratch and truly understanding something from the ground up.
What excites you about the Wisconsin RISE Initiative? I really appreciate that the RISE initiative recognizes that data science and AI methods are quite interdisciplinary and synergistic in nature. Having dozens of researchers across many departments coming onboard simultaneously and encouraged to connect with each other is a smart strategy for the University. I also find it significant and exciting that the departments bringing in AI & data science experts are broadly spread across the humanities as well as the sciences.
Does your work relate in any way to the Wisconsin Idea? If so, please describe how. Outside of the technological impacts of fundamental physics, I strongly believe that experiencing a feeling of awe has the power to shape our individual lives for the be)er and make us more generous community members. One reason I’ve chosen this career is that investigating the largest and the smallest scales of our Universe seems to be one of the more reliable ways to experience a feeling of awe and help inspire that feeling in others.
What’s something interesting about your area of expertise you can share that will make us sound smarter at parties? A physics dataset is a surprisingly malleable object. It’s not always obvious how best to translate the detector readouts into a dataset that we can analyze: is it a big table, or is it more like a set of points in 3D space? Could we instead think of it as a collection of images, sequences, or even language? Is it something more abstract? How we choose to represent our data — as well as frame the question we’re asking — in a computational analysis can have major effects on what we can learn.
Hobbies/other interests: Contemporary dance/theater/music, crossword puzzles, and highly amateur birdwatching