Dr. Jonathan Terhorst received his Ph.D in Statistics in 2017 from the University of California, Berkeley. He joined the Department of Statistics at the University of Michigan shortly thereafter as an assistant professor of statistics.
Jonathan’s undergraduate degree, also from Berkeley, is in economics. He worked as an economist for several years, and a significant portion of his job was related to data science. Jonathan became interested in understanding more about “how it all worked,'' which led him to return to Berkeley to do a Ph.D. in statistics.
Broadly speaking, Jonathan’s work is in the area of mathematical biology and statistical genetics. He aims to build statistical models of complex biological processes. That could be genetic data, or genomic data that analyzes how genes work together and are expressed. Jonathan’s methods have been used to study human evolution, natural selection, and cancer, and he has recently started working on related problems like metagenomics and understanding how HIV evolves within an infected individual.
Jonathan got into this area of statistics because he likes science and wants to be involved in it. His hope is that he can connect with scientists on the ground and help them use data to answer important questions related to evolution and human health.
According to Jonathan, one of the greatest challenges in his field is actually analyzing real data. “It’s not hard to create elegant, beautiful models that you can completely understand from a theoretical perspective,” said Jonathan. “But when you apply those models to real data, often times they don’t work, or they don’t produce results that are scientifically meaningful. What’s actually happening tends to be way more complicated than we’re able to understand.”
Jonathan grew up in the south, and lived in California for most of his adult life. Switching from a career in economics in California to statistics in Michigan may have been a significant leap, but it is a move that made absolute sense to Jonathan. “This is a great institution with a huge number of people working on interesting problems in statistics, biology, genetics, and many other fields,” he said. “Intellectually, it’s a great fit.”
Jonathan’s advice to budding statisticians and data scientists is to find a problem they are passionate about. “Statistics is a broad field, and you are lucky to have a lot of choices” of what to work on, he said. “Don’t just work on something because it’s trendy. Seek out a topic that you genuinely enjoy learning about – that is really helpful for staying motivated and productive.”