CSpotlight: Saving the planet with data science

Jared Willard is a computer science Ph.D. candidate committed to using his background in software engineering and mathematics to positively impact the world. Under the direction of his advisor Vipin Kumar, he is exploring the intersection of data science and environmental modeling. His current research includes using data mining techniques to track and predict water temperatures.

Why did you choose to pursue your Ph.D. in computer science at the University of Minnesota?

Short answer, I love Minnesota!

Long answer, I came out of undergrad with a mixed technical background in physics, applied math, and computer science. After realizing corporate software engineering wasn’t for me, I left to pursue a Ph.D. focusing on data science for public good. Minnesota was the most attractive option, given proximity to loved ones and the opportunity to work with Dr. Vipin Kumar as my advisor, who continues to do inspiring work on data mining in climate change research and environmental applications.

What inspired you to study computer science?

I started in computational physics as an undergraduate, but then decided to dive into the seemingly more applicable topic of machine learning, where I could also leverage my background in applied math. I figured working in interdisciplinary computer science applications would build skills conducive to working with different types of researchers from an array of disciplines. I realize the irony of that, seeing as a PhD is an extreme specialization, but the flexibility of data science careers and the ability to work on interesting problems during the Ph.D. is really what attracted me.

How did you decide to pursue research in environmental science and data science for your Ph.D. work?

I was introduced to this type of interdisciplinary research through working in Dr. Kumar’s lab, and throughout my Ph.D. journey, I’ve encountered many interesting research problems and inspiring people at the intersection of computer science and environmental modeling.

Tell us more about your research with the U.S. Geological Survey Data Science Team.

Currently, we are working on continental-scale lake temperature predictions using deep learning. We anticipate providing 40 years of surface temperature estimates for more than 185,000 lakes across the country, which will prove useful to other scientists studying physical, chemical, or biological lake processes. The effect of climate change on lakes is particularly alarming for ecosystems, for example. There are many more interesting data science directions being worked on at the USGS as well, like steam temperature, flow prediction and lake oxygen dynamics. The USGS Water Data Science team is great to work with, and I’ve learned a ton from them.

What advice do you have for other computer science students?

Be aware and educated about the social implications of your work, whether that be in engineering or research. Computer science isn’t as apolitical as people think.

What are your plans once you finish your Ph.D.?

My career goal is to become a scientist at a non-military government research lab or nonprofit doing things for the public good, whether that be environmental science, public policy, or something else. I would also love to get more involved in or support critical tech activism like Data and Society, the Algorithmic Justice League, Science for the People, the Tech Workers Coalition, or similar organizations.