Hey, that's my dad!

- By Molly Sharlach

Courtesy of Südhof neuroscience winners

Thomas Südhof with three of his children in Norway after receiving the 2010 Kavli prize in neuroscience. The children are (from left) Moritz, Sören and Leanna.

What's it like when your dad wins a Nobel prize? Moritz Südhof found out on Oct. 7 when his father, Thomas Südhof, MD, was named a co-recipient of the 2013 Nobel Prize in Physiology or Medicine.

A graduate student in computer science at Stanford, Moritz Südhof described how he learned about the news and discussed his father's influence on him in an email to Molly Sharlach, PhD, a science-writing intern in the medical school's Office of Communication & Public Affairs.

How did you find out that your father had won a Nobel prize?

I woke up to my housemate knocking at my door. I asked him what he wanted, and he said I should look at my phone. There were dozens of text messages and emails. And that's how I found out about the Nobel.

Of course, I was surprised. He just won the Lasker a month ago, and that was already a surprise and a great honor. Now the Nobel! Unreal.

I only have a superficial understanding of my father's field, so I am in no position to claim the prize was well-deserved. But I do know how much he cares about neurons and how hard he works to understand them, so I am thrilled he was awarded the prize. It is a recognition of the life-energy he has committed to his scientific pursuits. (And he was late picking me up from so many orchestra rehearsals when I was young — but I can rest comfortably now knowing that it all ended well.)

Do you have any stories about how your dad's work influenced you when you were growing up?

I remember one very particular moment with my dad that I think is characteristic of his attitude toward science and his children. In an effort to maybe turn me into a fellow researcher, he sent me to do some pipetting in the lab of one of his former postdocs, Rafael Fernández-Chacón — who is just a wonderfully amiable and dynamic man — when I was a sophomore in high school. He visited me in Rafael's lab in Seville, Spain, when he was in town one week, and he was fooling around with some lab equipment when he enthusiastically called me over and said, "Moritz! Moritz! Moritz! Look at this." He was so animated. "Isn't this just the most beautiful thing you've ever seen?" he asked. In the microscope, I could see the outline of a single neuron.

Did his interest in communication between neurons and the workings of the brain spur your interest in computer science and its social applications?

My father has an unbounded, voracious curiosity beyond neurons. it is really his passion for history, literature and particularly art that have impressed me and that define the intellectual relationship we have. And more than his work, it was my father's general attitude toward knowledge that was really influential when I was growing up. His desire to learn is inspiring. He taught me that the pursuit of knowledge is a vibrant, noble and rewarding thing, and he showed me that something interesting is worth studying just because it's interesting, and that something beautiful is worth admiring just because it's beautiful. Computer science is a wonderful field for someone like that because programming is a tool that feeds curiosity. For me, computer science is not an end in itself but an approach to problem-solving, and coding is a box of powerful tools that, if I know how to use them, augment my own capabilities and allow me learn and do things I otherwise couldn't.

Sometimes my work calls for me to use a neural network, which in computer science is a kind of machine-learning model that was inspired by the way neurons work. In those moments I always feel a bit closer to my dad's work, but the closeness is purely symbolic. Neural nets can be powerful, but compared to the complexity of the neurons and the synaptic processes that my dad deals with daily, artificial neural nets are just so simple that it's humorous. I would be embarrassed to claim to my father that I am proficient at using "neural networks."

About Stanford Medicine

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