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New faculty profile: Claudia Solis-Lemus develops statistical models to answer biological questions

Claudia Solis-Lemus joined the Department of Plant Pathology as an assistant professor in August 2019.

What is your hometown? Where did you grow up?
I grew up in Mexico City, where I did my undergraduate work at the Instituto Tecnologico Autonomo de Mexico in Actuarial Sciences and Applied Mathematics.

What is your educational/professional background?
I did my Ph.D. in statistics at the University of Wisconsin–Madison, and then a postdoc here as well in the Department of Botany. After that, I did a postdoc at Emory University in the Department of Human Genetics.

How did you get into your field of research?
I have always been a math person, passionate about mathematical theory, but also computational implementations. When I was a grad student in the Department of Statistics here at UW, I attended a seminar talk by professor Bret Larget about phylogenetic inference, and I was amazed by how probability and statistics could be used to answer real-life biological questions. I have been captivated by biological applications ever since!

What are the main goals of your current research program?
My research involves the development of statistical models to answer biological questions, balancing biological interpretability, theoretical guarantees, and computational tractability. In particular, my research deals with modern big data which are highly interconnected through graphical structures. Examples of my research involve the inference of phylogenetic networks to study reticulate evolution, comparative methods on networks to study the evolution of traits on hybrids, new sampling schemes to improve on Bayesian MCMC tools, as well as the application of such new tools to real-life datasets such as cultivated potato and carrot, Pseudomonas aeruginosa, Staphylococcus aureus, human endogenous retroviruses among others. Next-generation sequencing creates a big data reality that can make current methodologies prohibitive due to computational restrictions. My work produces a collection of new statistical methods with solid theoretical guarantees and efficient computational implementations that are adaptable to analyze the complex characteristics of modern big biological data.

What attracted you to UW-Madison?
Everywhere you look you find people doing amazing research, and they are incredibly friendly at the same time. In addition, Madison is a fantastic city to live in.

What was your first visit to campus like?
My first visit was when I moved for the Ph.D. Everybody had warned me about the cold, but for some silly reason, I was expecting it to be cold when I arrived in August. The hot weather was a pleasant surprise.

What’s one thing you hope students who take a class with you will come away with?
Statistics is not scary.

Do you feel your work relates in any way to the Wisconsin Idea? If so, please describe how.
My research in the Department of Plant Pathology has tight connections with agricultural problems in the state of Wisconsin, such as understanding plant pathogens, and the rise of treatment resistance (for example, fungicide-resistant fungal pathogens like white mold).

What’s something interesting about your area of expertise you can share that will make us sound smarter at parties?
Statistics exploits the power of big data, redefining the way in which we do science. One example in astroinformatics alone: the Square Kilometer Array is expected to produce an exabyte of astronomical data per day, which is more than twice the amount of data sent around the Internet daily! Statistics allows us to spark discovery out of the massive amounts of data that are being collected in every scientific field.

What are your hobbies/other interests?
I love triathlons (though I am super slow). I like to run, bike and swim. I love to swim in Lake Monona every week during summer, and bike through the amazing bike trails outside Madison. I also like yoga and bouldering, though I am an absolute beginner in both.