No Longer a Student

When I first heard about the concept of a Career Fair in my freshman year at Caltech, I half-joked to my friends, “I don’t want a career!” I came to college to learn math and science, and was quite honestly disgusted with classmates who would choose their course loads, student groups, or volunteer opportunities for the sole purpose of looking good on a resume.

This didn’t mean that I resisted growing up or planning ahead. I suspected I would want to go to graduate school, so I spent my first two summers doing research in my two favorite fields: math and chemistry. After all, this looked good on a grad school application for precisely the right reason: Experience doing research would prove to both myself and graduate admissions committees that I would thrive there.

During the rest of the year, I tried to learn all the things. I took the more difficult options for physics and biology requirements in addition to numerous advanced math and chemistry classes as a freshman and sophomore. I even sat in on the first few weeks of the main major-specific classes for astronomy and biology my sophomore year before the workload of organic chemistry lab caught up to me.

This same learning-centered approach would sustain me through the entirety of my double major in math and chemistry, the latter of which, as I would explain to my friends and family, I did “just for fun.” While this was of course a bit cocky to say on my part given Caltech’s famous difficulty, I preferred to be a model for a surprisingly uncommon motivation. As I noticed at graduation, in the entire class of 2012 at Caltech, I was the only student to major in two fields, neither of which were computer science or business, the two double majors one would most commonly add to look good on a resume.

While I don’t regret that approach in the least, my thinking shifted in a major way upon returning from a missions trip to Taiwan the summer after my sophomore year. Under a conviction that I was meant to serve the community around me (Christian and otherwise), I stepped back from the since-forbidden course loads I had sustained in my first two years. Instead, I poured my time and talent into tutoring and mentoring younger students, and leading the Caltech Christian Fellowship and ultimate frisbee team.

I had recognized that to God, learning is important, but serving is more important. Learning for learning’s sake, the approach I had more or less taken in my freshman and sophomore years, is actually fundamentally a selfish endeavor, especially when we’re motivated simply to look smart in our peers’ eyes.

But it wouldn’t be until my first year of grad school in the math department at MIT that I would more fully work out the implications of these priorities. As I started to understand what the research portion of being an academic entails, I immediately recognized the same problematic attitude that I had held previously: Pure mathematicians like I hoped to be simply want to learn things for their own sake, not for the purpose of improving the world in any way.

This really began to hit me when I was applying for funding from the National Science Foundation, an important step that many early graduate students and college seniors undergo every fall. As I struggled to justify why American taxpayers should care about my research findings, I balked at the common practice of simply making up applications that sounded reasonable. “Everybody does it,” people said, but then one of my reviewers got genuinely excited about one of these so-called applications and I immediately regretted it.

Fortunately, I didn’t win the award, so I didn’t have to live with the guilt of having gained something by deception. But it sparked a new drive in me, to spend the time I’ve been given doing work that at least offered path to improving something in the world. In short, I became an applied mathematician.

Initially, I felt like a fish out of water, and advocated aggressively for my fellow mathematicians to make the same jump I had, building something of a community through weekly gatherings of the math grad students interested in applications to machine learning. As grad school went on, though, I steadily drifted further downstream, from applied math to theoretical computer science to statistics and machine learning.

And now here I am, having finally been dumped out into the ocean of industry where I belonged all along.

So why did applied math not stick? As I said, I’m far from the only mathematician I know who decided to jump ship from pure math, but the vast majority were and are happy a step or two away. I’ve seen many of those friends go into variations on theoretical computer science and/or biological applications, and most are still planning on a full academic career. I’m one of the few who’s pulled that plug entirely, and I suspected pretty early on in grad school that this is where I’d end up.

I’ve previously described what I call the Hard Problem of Teaching: deciding what is actually useful to teach. The Hard Problem of Research is like it: deciding what is actually useful to study.

In a healthy research field, I would imagine an unbroken chain of collaborators connected to the engineers, doctors, programmers and so on who are actually engaged in directly useful work. Or, since a chain is not particularly robust, my platonic ideal of an applied research field would be a web of these collaborations, cross-disciplinary conferences, and the like.

For a variety of reasons, academia in the real world rarely lives up to that ideal. It’s incredibly common to hear talks with soaring motivations unceremoniously depart from those buzzwords to instead discuss what they really care about, never to actually connect the content of their work back to the way they sold it when asking for funding.

As usual, the fault is mostly with incentive structures. Publications are the primary currency in academia, most of which are written for and evaluated by the authors’ peers, not anyone at a different point in the spectrum. This attractive force clusters people to areas that others are already interested in, collapsing the ideal web to a dotted landscape of distinct silos.

This status quo also has some natural defenses against those who would wish to reform it. Pure researchers lean a lot on the historical successes of basic research, sharing stories from an era when academia globally was orders of magnitude smaller. In math, it’s always the unexpectedness of the number theory – cryptography connection. Such excuses aren’t actually inspirations but curiosity-killers, preventing academics from looking outside their silos.

The capitalist incentive structures of the business world are far from perfect, but at least they’re better-aligned with providing value to people.

I’m not going to pretend to have any major insights on this world of business after nearly three months of working at a startup populated by a bunch of recently former academics. But the main difference that I can identify between my life in grad school and today is the underlying motivation for the work I do. At Kebotix, we’re trying to use machine learning and robotics to accelerate chemical and materials discovery, and it’s pretty straightforward to connect that goal to what I’m actually doing on a day-to-day basis.

And that’s given me a much healthier work ethic than I had in grad school. Work is work, but it’s much more motivating with a goal we’re making tangible steps towards achieving than vaguely trying to provide something useful to someone based on a particular set of my own ideas.

There are other major differences. My work at Kebotix is fundamentally collaborative, working closely with our chemists and roboticists. We still have individual drivers to push forward various projects, but the credit for everything is shared.

Often the most successful academic work is also collaborative, but in the end, credit is doled out on an individual basis, both in terms of paper authorship and the ultimate goal of tenure. If Kebotix is successful, all of us will share in the rewards, aligning our incentives much better than in academia.

Enough about incentive structures, Sam. Tell us how you really feel!

There are certainly things I miss about being a student. The structure of the university is very conducive to making new friends, especially at a school as supportive of its student life as MIT. (I know! Not what you’d necessarily expect.) My fellow students who I’ve gotten to know have formed some of my closest friendships, and even my marriage.

I still haven’t really left per se, since with Grace still a student, we’re able to live in and serve as the social chairs for our married graduate dorm in Kendall Square. We’ve also remained part of the Graduate Christian Fellowship and are probably on a retreat with them right now as you read this.

Still, while I’m sad to be in the process of leaving the nest of school, I have to recognize that that support didn’t come for free. It’s paid for by someone, whether it’s the government or rich kids’ parents’ tuition. (Even if you TA, the tuition coverage that affords is effectively subsidized by the tuition of the students that you’re teaching.) It’s high time I gave others access to those opportunities.

My time as a student was sweet, but it’s finally come to an end. Farewell, school!

5 responses to “No Longer a Student

  1. Maria Gillespie February 15, 2019 at 10:31 pm

    Glad you found the path that feels right for you! Congrats.

    One thing I’d argue with, philosophically, is that doing pure math for it’s own sake is an intrinsically worthwhile endeavor for some subset of humans to pursue, similarly to music or dance or other forms of art. So, rather than it being a problem with academia that we lie about the applications of our work, I feel it’s a problem with the NSF and/or other funding organizations for insisting on concrete, immediate applications. Perhaps pure math should be funded the way arts are funded instead, though math rides and interesting boundary between art and science that makes it hard to classify. In any case I don’t feel it’s selfish to commit one’s life to providng the world with beautiful proofs of fascinating theorems.

    That being said, working on machine learning in industry is also not selfish. 🙂 I hope you occasionally post about what you work on here so I can read about it!


    • Sam Elder March 1, 2019 at 7:21 pm

      Math-as-art is a totally reasonable hobby, but likely wouldn’t employ more than a small subset of the mathematicians, like yourself, who write for a popular audience. Martin Gardner types could perhaps make a living off of their books in recreational mathematics, but do you think you could possibly live the life of an artist? If you bundled your original math research into a series of popular level books, do you think they would sell enough copies to sustain your livelihood?

      Professional musicians write and perform music that the broader public enjoys, and are compensated accordingly. The government doesn’t need to step in and fund the entire music industry. The trouble with math-as-art is that the vast majority of research programs in math aren’t accessible to the wider public.


      • mariamonks March 3, 2019 at 4:27 pm

        You make good points, and I have two responses. First, the vast majority of art that is created is not appreciated by the general public. I personally don’t enjoy art museums all that much because I don’t know much about visual arts and so I don’t get much out of staring at the pictures or sculptures. I do know a lot about music and therefore can enjoy many forms of it, but there are many people who dislike classical music or jazz or other less popular styles, because they are not “accessible” forms of art to the layman. Such musicians are usually not “compensated accordingly”, as you say – they usually have a day job or teach music to get paid, unless (in rare cases) they make it big.

        I would say that the music and art that sells is comparable to sudoku puzzles or popular math books. It’s good that that kind of thing exists, but it’s *also* valuable to have some government and/or university funding for the arts so that artists can have the freedom to push boundaries in ways that may not immediately sell.

        Second, which perhaps I should have argued in my first comment: Math is not just art, it also is a science, and in fact forms a theoretical framework on which much of the physical sciences build. The applications of a mathematical result may not be apparent until many years after the result is discovered, but this lack of immediacy does not render mathematics useless. It was useful, for instance, to have differential geometry all built before Einstein came around and came up with general relativity. Did the differential geometers spend their time trying to comb the hair on a ball? Yes. But that “play time” of the mathematicians who preceded Einstein’s time turned out to be very valuable.


        • Sam Elder March 9, 2019 at 9:58 pm

          That’s true; I suppose that classical music could be an appropriate analogy to pure math. Both do take similar perspectives towards cultivating their art, and have a degree of dependence upon teaching, government assistance, and, especially today, wealthy benefactors to support themselves.

          Extending the analogy further, it’s also true that classical music forms the basis on which most of popular music is based (instrumentation, sheet music, chords, etc.), but the two worlds have grown increasingly far apart recently. Pure math as conducted today is similarly fairly divorced from applications, or at least indifferent to them. I mentioned this in the original post, but given how much academia has ballooned in the 20th Century, so much low-hanging fruit has already been picked that I think it’s very likely that the vast majority of pure math research done today will never see practical use.


  2. Pingback: It’s Okay If They Don’t Remember You | The Christian Rationalist

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