This week, I spoke with Ken Ono, former STEM Advisor to the Provost at UVA, current Founding Mathematician at Axiom Math AI.
Former Vice President of the American Mathematical Society, member of the US National Committee for Mathematics, chair of the Math Section of the American Association for the Advancement of Science, and board member of the National Academies of Sciences, Engineering, and Medicine.
As well as producer for the film The Man Who Knew Infinity and 2022 Miller Lite Super Bowl commercial actor.
The Rundown:
COLD OPEN: Raised in a post-WWII Japanese family, mathematics misconceptions, UVA Olympic science to AI startups
TURNING POINT: The flawed ways we measure potential and finding identify
STEAL THIS: Do you feel like you’ve earned it?
INDUSTRY INSIDER: Why AI struggles most with general topics, whereas niche ones are trivial
IF I WERE YOU: Don't focus so much on the next achievement that you miss the opportunities right in front of you
COLD OPEN
How Did You Get Your Start?
Like most people, my story is quite complicated.
My father was a mathematician who came to the U.S. from Japan after WWII.
He came from the country that bombed Pearl Harbor, and despite being raised to believe the United States was the enemy, it ended up being heaven on earth for him and my mom – at least academically.
He was recruited as a postdoctoral faculty member at the Institute for Advanced Study in Princeton, rubbing shoulders with people like Kurt Gödel, Albert Einstein, and Robert Oppenheimer.
Yet outside the walls of the math building, my parents couldn't escape the fact that they were Japanese living in the U.S. ten years after the end of WWII. It was difficult.
So, they thought the only way my three brothers and I could succeed would be in similar academic settings my father had thrived in.
My oldest brother went on to become a professional pianist at Juilliard. My other brother got a PhD in biochemistry and was the president of the University of Michigan.
I was the youngest with a talent in mathematics, and my parents thought I had to be a mathematician. I hated it.
In second grade they signed me up for the SAT math test. Here I am now, at 57, and I’m still doing math. If you asked me how I got here, I’d say I tried my hardest to be anything but a mathematician.
As a kid, I avoided it because I equated meath with just grades and test scores.
I was not a “good” student by any means. I graduated from the University of Chicago with a 2.7 GPA. I took pride in putting in the least amount of effort in to get by.
Without the mentors I met along the way who saved me, I wouldn't be where I am today. One of them, 20th century mathematician named Ramanujan.
When I was in college, I saw a TV special about his unparalleled math ability, despite having no formal education. It resonated with me.
Learning his story and later reading his biography in graduate school, I began to view math differently – looking for the beauty and science as opposed to the goal only being to publish papers.
About 10 years ago, I ended up being a producer on a film about Ramanujan called A Man Who Knew Infinity.
I began at UVA as a math professor back in 2019. I held many positions including the Chairman of the Math Department and STEM Advisor to the Provost.
While at UVA, I worked closely with the swim team, applying the scientific method to faster lap times, having the honor to go to the Paris Olympics in 2024 with the team.
In 2025, I left UVA to be a Founding Mathematician for my former research student Carina Hong at her AI startup, Axiom.
If you want to read my full story, I wrote a book about it called My Search for Ramanujan: How I Learned to Count.
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TURNING POINT
What’s A Challenge You Faced Early On?
We live in a society that’s built and based on metrics that aim to measure potential.
Often, though, our tests fall short. Does anyone really think the SAT captures someone's potential? Or the student with a 4.0 is that much better than one with a 3.8?
We’ve replaced getting to know someone for their character and achievements with whether or not they check the right boxes.
Getting through that reality was a big challenge for me. It certainly impacted me in the 80s when I was in high school and affected my ability to find my identity as a scientist later on.
GPAs and scores may seem important in the short term, but if you're 30 and still talking about your SAT, you’ve missed the point.
Your peers are important, but don't forget that you are the most important person in your life.
You may get advice from friends, professors, and family members, but that's only advisory. The person whose advice matters the most is your own.
STEAL THIS
What’s A Question You Love To Be Asked (Or Asking)?
When my PhD students are entering their final phase of work, they’re thinking, “I have to pass my oral exams, I've started writing my thesis, and then I have to defend my thesis.”
All practical next steps. What I do is ask them something completely unrelated.
I say, “Do you understand now that pretty soon someone is going to call you professor?”
“How does that feel? Does it feel like you've earned it?”
When I ask that question, it's always the point where the student says, “Yeah, you know what, I've earned that.”
I don’t always have a single question to ask everyone, but whatever it is, I want the other person to be excited about what their answer is.
INDUSTRY INSIDER
What Do People Misunderstand About Being A Mathematician?
If you're not trained as a pure mathematician, some of the questions we consider might seem kind of out there. We aim to find the truth – questions we can answer with no possibility of exceptions.
In some cases, we work very hard to prove theorems where the evidence towards one side is already overwhelming. Some ask, “Why bother trying to prove something when the first thousand examples fit the bill?” “Why explore into the realms that may never coincide with human experience?”
A few years ago, I would have said the answer is to search for beauty and truth. Make no mistake, with that alone, we've come to discoveries as influential as the internet. But now we're in a post-ChatGPT world, and my justification has changed.
As everyone knows, large language models, ChatGPT, DeepSeek, Perplexity AI, Google Gemini, these entities make mistakes.
The way pure mathematicians value attention to detail and the incessant need to prove the claims they make, is exactly what we need when teaching these models how to check their work.
It’s not just about improving the models, it’s developing new kinds of computer science, new kinds of AI.
Let's say you ask a model a question in a very niche field. There may only be 5 or 6 papers on the subject, so the model can very quickly find them and provide an answer.
We used to view these niche problems as the hardest, but now with AI they are seeming more simple to solve.
Yet, for AI, some of the hardest problems are where the literature is crazy saturated, so the models don’t know where to go.
They’re stuck in a maze because there’s so much information out there about general topics, so knowing where to find the truth is much more difficult.
When you understand that, hallucination for seemingly obvious truths makes more sense.
IF I WERE YOU
Do You Have Any Advice For Students?
If you're at UVA now as an undergraduate, take advantage of all that you can so that you don't have regrets.
Sign up for clubs, go to office hours, make friends.
Our students are high achievers, always worrying about the next thing. “How do I get the right internship?” “How do I get into the right graduate school?”
I won't deny the importance of those endeavors, but don't focus on that to the extent that you miss out on all the other opportunities that are here.
CLOSING TIME
What To Do Next
Reading is great — but putting yourself out there, meeting new people, and finding opportunities is what this is all about.
4 things to do right now:
Find a UVA alum and send them a cold message.
Follow up in a week if they don’t respond.
Prepare for the meeting, and talk to them
Explore a new industry:
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