About me

Hello! This is a work in progress, but here you can find a copy of my thesis, or click here for my CV (refereed publications listed at the end) as of March 2024.

During the COVID-19 lockdown, some of the virtual talks I gave were recorded and are publicly accessible: Click here for a talk I gave as part of the Fluids and MHD seminar series at Leeds on fingering convection/thermohaline mixing in MHD, or click here to see a similar talk I gave to the Transport in Stars 2021 KITP conference. Click here to see a talk I gave about my PhD research to the Staircases 2021 KITP meeting (I’m the third speaker in the recording; note this was aimed at a high-level audience, so I skipped a lot of introductory material that I usually cover in talks). Click here for an asynchronous talk I recorded to introduce participants of KSPA 2020/2021 to myself and some of my recent work at UCSC (note this was intended to be very short and informal to serve as a baseline for subsequent discussions, not a formal talk).

Click here to see my APS-DPP 2021 poster on nonmodal growth in MHD KH.

I’m a Hale Postdoctoral Fellow at the University of Colorado, Boulder. Before this, I was a postdoc at the University of California, Santa Cruz (UCSC), working with Prof. Pascale Garaud in the Applied Math department. Previously, I was a PhD student in the Physics department at the University of Wisconsin-Madison working with Profs. Paul Terry and Ellen Zweibel, and as an undergraduate I studied physics and math at the University of Oregon.

My research interests include astrophysical/geophysical fluid dynamics and plasma physics, particularly turbulence driven by fluid and plasma instabilities. Turbulence is found in a wide range of systems, including stellar interiors, galactic outflows, protoplanetary disks, planetary atmospheres, Earth’s oceans, and nuclear fusion devices. In each of these systems, turbulence can significantly enhance the mixing of heat, chemicals, and momentum, which can lead to a variety of important effects, like influencing the lifetime of a star, or reducing the efficiency of a fusion device. Despite the importance of turbulence in these systems, quantitative, predictive models (like a formula for exactly how much turbulent mixing you get in some region of a star depending on things like temperature and density) remain elusive, and are in high demand – engineers would love to be able to accurately predict turbulent losses before they build the next fusion device.

I work towards these models by using a combination of numerical simulations on supercomputers as well as analytical calculations. Ideally, we’d like to build a model from first principles that can be tested in simplified systems that are possible to simulate, and then extrapolated to realistic systems that even modern supercomputers can’t simulate.

Currently, I’m studying MHD turbulence driven by shear flow and by double-diffusive convection (DDC). We hope to either provide reliable, simple models that can be included in something like MESA, or predict observable consequences of DDC so we can identify which “missing mixing problems” are due to DDC and which ones require a different explanation.

I welcome participation from students. This kind of research is amenable to involvement from students with a variety of interests and backgrounds (e.g. projects with lots of programming vs little programming). If you’re a UCSC student interested in working on this kind of stuff, don’t be a stranger! Please reach out to me and/or Prof. Garaud.

In my spare time, I recently got way into windsurfing, and sailing more broadly, including keelboat racing, and sailing on 420s, lasers, and E-scows. When those activities aren’t accessible I have a lot of fun playing basketball very poorly, salsa dancing, and I enjoy a good hike or bike ride.