Applying to graduate school
The Meta-story
Meta
adjective: referring to itself or to the conventions of its genre; self-referential. 1
I don’t think there was, like one would like to imagine, a “moment of revelation” for when I decided that I wanted to apply to grad school. Unlike some other stories you’d hear, it wasn’t that I always thought that I would one day go to grad school either. My opinion is that the real reason we, as humans, decide to do something is often much more complicated (and opaque) than the story we tell others, ourselves, and eventually convince ourselves is the case.
In the same vein, there are many people who write posts that give advice on applying to grad school. I owe much thanks to their work — see “Other Links” on the right for some I felt was really helpful. But I also cannot help but feel that advices are often too distilled: the advice-giver reflects on their experiences, thinks about the larger picture, and summarizes them into their advices. The downside of this process is that a lot of details are lost in the process, and inferring the intended situation for which a piece of advice is applicable is quite non-trivial. 2
Given the wealth of online resources these day, especially for applying to graduate schools in CS, I feel that the most helpful thing for me to do is to fill in the void of such lost details — so instead of giving advices from the unqualified position of a junior graduate student, I’ll try to write about my experiences: how I started doing research, what my application season was like, etc.. Hopefully the experience can be the medium of implicit advices, from which you get to decide what to take away.
Computer Science?
I learned some programming — which amounted to def, return, for, if, and else in Python — in high school, but nowhere near seriousness. In fact, I started college as a mechanical engineering major, and did it (mostly) for my two years at Rutgers. It wasn’t very fun. Most engineering programs in the US share a common core during the first 2 years, which covers the basics in a broad range of STEM topics. I think it’s because of ABET accredidation. If you’re an engineering major that wants to “build stuff”, you’ll be fairly disappointed during these 2 years.
The final straw (I think, in retrospect) was a mechanical engineering internship I did. I can’t complain much about the company or the projects I was tasked to do — I had an overall fairly positive experience — but there’s also the feeling that traditional mechanical engineering companies are simply not where “things happen”. It did not feel like a career I wanted to have.
Computer science, in contrast, is indeed where “things happen”. I was tranferring to Brown the semester after the internship, so it was a good excuse to start something new. I did the necessary placements, and took intro to CS and deep learning3 (a very weird combination) in the first semester of my junior year.
… and Language?
Interestingly, I think what’s most important to my starting my current research was the humanities electives required by ABET: during my first year at Rutgers, I took and immensely enjoyed 2 philosophy courses, logic and philosophy of language. Philosophy of language, in particular, opened a new world for me. I was fascinated by the project of introspectively characterizing our linguistic capabilities. Taking the (very well given!) advice of the need to have some STEM-humanities balance, I took a philosophy of language seminar, Sense and Reference4, the same semester as my first CS courses. It struck me that artificial systems — GPT-3 has been out for 2 years at that point — did not satisfy most of the assumptions we use when analyzing linguistic creatures, yet they seem to master language so well.
The same semester, driven by the fear of not having something to do during my junior year summer, I started looking for research opportunities. One such attempt was going to an ask-me-anything session hosted by Ellie, during which I unloaded my philosophy of language questions re. language models towards her. I enjoyed that a lot, and started dropping in to the lab meetings.
After a while, someone in Ellie’s lab asked for help on a new project. I volunteered5, and started working on it. Getting the first toy model to train took 3 months. I got a research assistantship during the summer, and getting the first proof-of-concept to work took another 2 months. I was lucky, though: when the start of my senior year approached, I had a project that was taking shape. The project was a great reflection of my interests: a union of philosophical questions about artificial and natural intelligence and technical neural network research.
Applying
Much like everyone else’s research projects, there was a lot of head-scratching and a lot of frustration involved in my first project. But the sense of fulfillment of finally getting something done, and more importantly, getting something new, something I cared about done led me to think that maybe research could be a career past graduation. I also realized that I had what’s minimally required to apply to grad school: I liked what I did, so I could apply to do similar things and use my experience to back up the application.
Late September 2023, I decided to apply: I wasn’t confident about getting offers6, but like a lot of other things in life, the cost of failing is sufficiently low so it’d be foolish not to try. I asked my advisors what programs/people she would recommend, added in authors of papers I read and admire, and built a list. I only included schools I actually want to go (which is against best practices given by this article, for example, if what you want is to have a place to go). As a remedial strategy, I decided that I will also apply to full-time jobs. It’s nice that the timelines are somehow separated — deadlines for PhD programs are usually in December, when companies slow down interviewing/hiring, and the biggest recruiting season is early fall, before grad school applications start. This choice added significant work, and I did not get a full-time offer (mostly due to my disastrous technical interviews), so I can’t comment on how advisable this strategy is. But I think it’s worth considering.
I also chatted with some graduate students about their experiences: it would seem that at Brown, people are in general fairly happy. No horror stories of unbearable pressure or terrible advisors, and many recommends it as a chance to do something you believe matters. That resonated with me a lot: I still think doing a PhD is what maximizes your chances of doing something you care about and think matters.
Despite being a habitual procrastinator (I wrote my Brown transfer essay 3 hours before the deadline!), I set a hard deadline for my SoP: first draft before the first day of November, and miraculously met it. I then went through a few revisions， mostly asking for comments from friends, asked around for recommendation letters7, and submitted my applications during finals week.
Post Application
There was a lot of anxiety after I turned in my applications: every email notification would make me jump, and I checked GradCafe multiple times a day. I quickly found out that I’m suffering from too much information: if a school I applied to has updates on GradCafe, I would start wondering if that means I’ll get rejected. In reality (and I think we all know), there are just way too many variables and one can’t reliably predict what’s behind the scene. I stopped polling GradCafe and social media sites for updates in January, and my anxiety lessened significantly.
I eventually started getting interviews — they can happen at any time, but mine turned out to be early — and enjoyed chatting with the professors that interviewed me. It felt a lot better than job interviews. Instead of being interrogated for technical details, My interviews are more like research chats8. If there’s a shared passion/niche in research, the chat usually goes quite well. I also tried selling people my project ideas.
Then in February and March, I went to school visits. I really enjoyed talking to people: grad students, professors, other visitors. And on a range of topics: my research, their research, where the field is going, where my (their) life is going, how my (their) life currently is. All of the trips are paid for, which is a nice cherry on top as well. I also found keeping notes very helpful: these chats are much more effective if you keep a list of questions, as well as whom to ask. For example, you might want to ask for comments on your potential advisor from their students, other students in the department, their collaborators, and themselves. It’s also very useful if you keep notes of their answers — maybe do that when you come back to the hotel at the end of the day. There are details that easily get lost if you don’t note them down: potential collaborators, papers to check out, bureaucratic red tape, etc..I personally find the notes really useful when making decisions.
But beyond obtaining information, I think you get a better feeling of what it’s like9 to be there at a school visit. The more you ask and experience, the clearer your picture is going to be — and I think that’s the best way of deciding where to go: imagine yourself being at those places, which one do you like more?
I talked to a lot of people (maybe too many) while trying to make the decision. In retrospect, the choice was pretty clear to begin with, I was just indecisive and wanted the best of both worlds. I think this is the case for many important decisions we make: if you picture yourself after choosing different options, the choice becomes a lot more clear. I sent response emails in early April, and accepted my offer officially — the official deadline is April 15 and I think you shouldn’t get pressured to decide early, but it’s also good to accept as soon as you have decided.
Afterwords
I am currently writing this blog post in my apartment, half a year after coming to Yale. I am, so far, enjoying my grad school life. I think there was a lot of luck (and privilege) involved in my application process, and we shouldn’t try to summarize too much from past examples. But in light of all the uncertainties, it’s even more important that one explore — had I not taken philosophy of language, I wouldn’t be here now — and attempt — had I decided too early that I wasn’t qualified, for research or for grad school, I also wouldn’t be here. I consider myself an unlikely and atypical applicant, and I suppose there are two sides of this story: part of the hope of writing this post is to give some other atypical applicant like myself a reference data point, but the other part is that not having a reference data point doesn’t mean something shouldn’t be attempted.
You can find my SoP here. I’m also happy to chat more.
Footnotes
Google English Dictionary, provided by Oxford Languages↩︎
There’s the saying that “for any non-trivial piece of advice, the opposite is often also true”. I don’t know what the source is, but I deeply feel that this is the case.↩︎
Oweing to having double majored statistics at Rutgers, I actually did have the background needed for deep learning.↩︎
The course gets its name from Frege, and it’s also an amazing course.↩︎
Without knowing Pytorch (I only learned Tensorflow) or Huggingface↩︎
One main worry was the fact that I had only started CS a year ago, and never did the classic sequence of requirements. That turned out to be less important that I anticipated.↩︎
A huge headache and stress factor, especially if your recommender is not very responsive.↩︎
I’ve seen some people prepare presentation slides about their research projects. I think this can be helpful, but if the default is to “chat about research”, my opinion is that presenting with slides actually kills the atmosphere and may lead to people fixating on technical details↩︎
How your life will be like is very much a type of qualia: borrowing classic philosophical theories, we can’t know this unless we lived it, and visits give you a good taste.↩︎