Mathematics, PhD ('24)
Who is your employer, and where are they located?
Cooperative Institute for Research in the Atmosphere (CIRA), working at NOAA's Global Systems Laboratory in Boulder, CO.
What is your job title and what kind of work does it involve?
Fire Weather Applications Researcher (Research Associate III). I am working on developing codes and models used to improve high resolution weather prediction.
What sparked your interest in your area of study?
Coming from a background in high school math education, I started the math PhD program at UNL with an open mind. I knew I liked math and wanted to learn more. The workload was a lot to manage and the learning curve steep, but I especially enjoyed analysis with Prof. David Pitts.
In my second year, I took a partial differential equations class and remember thinking I could do that every day and stay interested. It was when I heard my future advisor, Prof. Adam Larios, speak about turbulence that I was really hooked—a challenging interdisciplinary subject that connects theoretical beauty to tangible world problems. When school was difficult, that connection is what kept me in it.
What do you see as the value of your major(s) or CAS degree?
I still refer back to the notes I took in my graduate classes. That is a testament both to the relevance of the courses my advisor pushed me to take and to the habits I developed while working through them.
My advisor encouraged me not only to continue taking classes within the math department, even retaking courses with different professors, but also to take courses in physics, mechanical engineering, and atmospheric science. That exposure gave me multiple ways of thinking about the same problems, which has been especially valuable in fluid dynamics.
Altogether, that training gave me a strong foundation for an interdisciplinary career, and it's something I rely on regularly in my current work.
Were there any other people, activities, or events from your time at UNL that helped you get to where you are now?
I'm not sure I would have made it through a PhD at another institution. I came in without as strong of a mathematical background as I thought, and that became clear early on. The professors in the math department helped me push myself without burning out by making equitable accommodations. I was allowed to retake my qualifying exams one at a time, and encouraged to take cross-listed undergraduate courses so I could strengthen my fundamentals while having more time to focus on my graduate work. I was given options even when I felt like I had run out of time and energy.
The culture in the UNL math department places a strong emphasis on teaching using studied best practices, especially the idea of meeting students where they are (thanks in part to Prof. Nathan Wakefield). That approach made a real difference for me. It created a supportive, equitable environment where I could grow into the level expected of a PhD student.
Tell us about the path you took to get to where you are today in your career and how you applied your education in your major(s) or area(s) of study to get here.
When I started applying for jobs, all I knew was that I wanted to work somewhere I could continue learning about turbulence. I applied broadly to labs, industry, and postdoc positions, and got great advice on my application materials and interview skills from my advisor and the math job search seminar.
I had also built experience through internships and summer schools, and I started applying a year earlier than I needed to. I'm glad I did, it's a lot of work to be on the job market, and it changes every year.
I ended up in a role that was better than I could have hoped for: working on weather applications while continuing theoretical research and learning from a skilled computational physicist.
Starting out, I faced another steep learning curve. I had limited coding experience, and none in C++. I was grateful for my graduate training because I had been through a similar transition in my first year. I reflected on what it had felt like—the uncertainty, the panic, the extra work it took to just catch up. I also knew that each year brought more confidence, and I thought about the level of ease I had reached after just five years. That perspective helped me settle in, apply old skills while gaining new ones, and even enjoy the early stages. Now, just two years in, I'm proud of what I've learned and accomplished so far, and I look forward to helping shape the future of numerical weather prediction.
What are your future professional goals?
Keep learning about fluids and computation, and continue building connections between theory, modeling, and applications, especially in ways that improve our ability to model and understand complex environmental systems.
