Dr. Paul Constantine is an assistant professor and one of 19 new faculty in our growing department. Paul’s background is in computational mathematics and his research is in developing and analyzing methods that seek to identify exploitable low dimensional structures in complex computational science models. Paul is also my advisor, the best professor I’ve ever had, my strongest advocate, and one of my biggest role models. The words below are incapable of capturing Paul’s contagious enthusiasm and energy— we are beyond lucky to have his influence in our department.
“In mathematics you don’t understand things, you just get used to them.” - John von Neumann
What is your path in getting to CU Boulder?
It’s easy to create indestructible giants of our professors and mentors, to revere them as scientific prodigies who have always had their paths carved out. As a student this can be discouraging when we encounter doubts or struggles. Paul’s story helps shatter this unhealthy mirage. Paul had a spotty undergraduate career and dropped out to pursue his passions as a musician and travel Europe. Eventually he graduated with a BA in mathematics and a minor in music from the University of North Texas, and went on to work as an actuarial analyst and software developer. Paul then received his MS and PhD from the Institute of Computational and Mathematical Engineering at Stanford, worked as the John von Neumann fellow at Sandia National Labs, and was a postdoc at Stanford. Most recently Paul was an assistant professor in the Department of Applied Mathematics at the Colorado School of Mines, where he left (with me, his two PhD students, and his postdoc!) to join the wonderful department here.
What are some of your hobbies?
Paul loves music, plays the drums, percussion, and electronics, and is looking to join or start a band! Paul also loves embarrassing himself at karaoke, playing soccer, ping pong, and traveling.
What are some improbable facts about you?
Paul’s grad school band played with the musician K.Flay, who just got nominated for two Grammys. He went to high school with Jessica Simpson and his mom is a Lutheran minister. He also didn’t finish his first calculus class until the summer after his freshman year of college.
If you could make sure everybody in the world knew one thing, what would that one thing be?
Imagine the world if everybody knew how to think about problems like optimization problems, with objective functions and constraints. Everything from policy decisions to personal arguments would be more intentional and clear.
What part of what you do makes you most excited?
Paul is excited by finding low dimensional structures and developing methods for finding them. Equally satisfying is being able to interpret these structures in context of the problem, and his research allows him to work on problems across disciplinary lines. “Interdisciplinary communication is a euphemism for talking to people.” Paul loves working with people with different sets of interests and problems. He is excited to understand and help solve these problems with mathematics, statistics, and computation to make an impact .
What advice can you share with us?
Sympathize with those evaluating you: Everyone is going to be evaluated throughout their careers, whether it be for a fellowship, grant, paper, job application, or tenure. Understand what those evaluating you are looking for, what their constraints and objective functions are, and empathize with them. Practice epistemic humility: Be humble about the degree to which one can really know things. Remember this in all discussions and interactions and understand that you might be wrong.
Not all knowledge is scientific knowledge: There are things in the world that cannot be quantified. We sell technical degrees as teaching people how to problem solve. This is baloney, otherwise we’d see headlines everyday about mathematicians solving world hunger or scientists ending homelessness. Quantitative analysis is essential in solving in a problem, but it is not all of it. We must learn from and understand others’ perspectives and knowledge.
Icebreaker Suggestions:
How many dimensions is high dimensions? “Also, I would love if someone would send me a definition for artificial intelligence or machine learning.”