From Data Sets to Moth Brains

Quick Study
Photo by Tony RinaldoPhoto by Tony Rinaldo

J. Nathan Kutz RI ’13—known among his peers for his sharp suits and love of espresso—uses methods and ideas from applied mathematics to address a variety of problems in science and engineering. Through his research, he hopes to achieve a modern mathematical framework capable of advancing theories of information processing, statistical data analysis, and data-driven dynamical systems in areas as diverse as climate modeling, epidemiology, and neurosensory systems.

Who are your heroes?

Early in my career, I was fortunate enough to work briefly with James P. Gordon of Bell Laboratories. The more I got to know him, the more I wanted to be like him when I grew up. He was an exceptional scientist who combined theory and experiment in his work, much as I am attempting to do. Everybody who knew Jim thought the world of him; he was a distinguished gentleman and a class act of the highest order.

Describe yourself in six words or fewer.


Disciplined, kind, warm, trustworthy.

Which trait do you most admire in yourself?

I’m very disciplined, and that discipline has helped carry me through dry spells and a generally overbooked schedule.

What is your most treasured possession?


My espresso machine. It has allowed me to be an amateur barista so that I can develop my latte art. In fairness, I am looking at dumping my current machine for an upgrade . . . so much for “treasured.”

Were your life to become a motion picture, who would portray you?

I would hope for George Clooney—that would certainly be a big upgrade.

What inspires you?

Discovery and creativity. Both these activities involve taking risks and failing. So perhaps when an idea finally works, it feels fantastic and helps inspire additional ludicrous thoughts. Also, most things Italian inspire me (food, wine, gelato, clothes, cappuccino . . .).

Where in the world would you like to spend a month?


Rome. It is full of all the simple pleasures I love. It also is so incredibly inspiring to see the history and art that have shaped the world.

Name a pet peeve.

Loud public cell phone usage!

What is your fantasy career?

I would love to be as funny as Jon Stewart so that I could host the Daily Show. Plus I could still wear a suit and use all my quantitative skill set to expose some of the absurdities of government and politics.

Tell us your favorite memory.

Playing with my two brothers on the beaches of Rio de Janeiro as a kid. Those were halcyon days.

Your work makes a connection between Pablo Picasso’s cubist work The Guitar Player and a George Washington–shaped chicken nugget that sold on eBay for $8,100. Can you briefly explain that for our readers?

Experiments suggest that our neurosensory systems are especially well suited for stereotyping input data into well-known (recognized) patterns of neural activity. In particular, sensory systems attempt to bin and classify data into things we “know.” Thus, a randomly shaped chicken nugget or a highly abstracted set of lines and colored boxes by Picasso can cause our brains to reconstruct George Washington or a guitar player in our neural systems of “recognition.”

How is it that you—a mathematician—work in the lab with neuroscience postdocs?

Like many great things in life, my first serious foray into neuroscience came about from randomness: a chance encounter with a new biology faculty member (Jeff Riffell) at the University of Washington at a lunch for about 500 people that neither of us wanted to attend. After the usual pleasantries, and within five minutes of our meeting, we had started an intense dialogue about his neural recordings of moth olfaction. That same week we met again to continue our discussion and develop 
a collaborative strategy for quantifying the neurosensory signal processing of the antennal lobe of the Manduca sexta moth.

Things simply took off from there. As biology grows more and more quantitative, especially because of the rich data sets now being collected, partnering with mathematics has become natural, if
 not critically necessary, for progressing into the future.

 

Search Year: 
2013