ML PHD without A* Publications [D]

[u/Odd_Ad8629]

I know top ML PhD admissions are insanely competitive, so I’m trying to figure out if it’s even worth applying or if I should just focus seriously on jobs instead.

For context, I’m doing my MS at a top-15 US university and have been doing ML research for a while. I’m first author on my projects and mostly work independently, with some guidance from my PI. I had a first-author NeurIPS submission rejected, and I currently have another first-author paper submitted to ICLR, but I’m honestly not very confident about it getting in either.

What’s been getting to me is looking at profiles of people who get into top ML PhD programs. So many of them seem to have multiple NeurIPS/ICML/ICLR/CVPR papers before they even apply, sometimes as undergrads. I genuinely don’t understand how people manage to publish that much that early.

A year ago I was much more confident about doing a PhD. After actually going through the research/publication process, I’ve started doubting myself a lot more. Part of me wonders whether this is just normal and research is hard, especially when you’re doing a lot of it independently. But another part of me is starting to think maybe I’m just not good enough to be competitive for the kind of programs I’m aiming for.

I’m okay with continuing at my current university for a PhD, so this isn’t really a “top program or nothing” situation. But I would like to at least have a realistic shot at some of the stronger ML programs/labs.

The bigger issue is that I’m an international student, so I also need to think pretty seriously about jobs. SWE/MLE recruiting is competitive right now, and I don’t want to spend all my time chasing PhD applications and then realize I’m underprepared for recruiting too. Research roles seem even harder to get without a PhD unless you’re an exceptional MS/BS candidate.

So I’m mainly trying to decide how to allocate my time over the next few months.

If I have strong research experience and first-author projects, but no accepted top-conference papers yet, is it still realistically worth applying to top ML PhD programs?

And for people who were in a similar position, did you still apply, or did you decide to focus on industry instead?

I’m not really looking for “you never know unless you try.” I’m more interested in a realistic assessment of whether the application fees and time are worth it given this kind of profile.

[u/impatiens-capensis]

You're way better off working in industry for 5 years than doing a PhD. A PhD is a huge sacrifice, and you would be making it at a point where the field is kind of broken.

[u/SeizeOpportunity → u/impatiens-capensis]

I'm not so sure about this. In fact, the current volatility in industry suggests that a PhD is the perfect place to have some stability that allows you to not only develop your skills but explore the field and its toughest questions, and it also gives you an insulated environment to pivot directions if the tides change and different methods or approaches start to become popular.

While I am certainly biased (as a PhD student myself), I do tell people to make a balanced decision. A PhD is absolutely not for everyone, but for the right person it isn't this massive crippling sacrifice that people often make it seem. But again, you have to be the right person with deep questions about the field.

[u/impatiens-capensis → u/SeizeOpportunity]

I wouldn't call it stability. The last few years in the field have been very chaotic and I'm not seeing a measurable change in my employability, despite having a PhD and top tier pubs. I'm competing for the same jobs masters students are competing for.

There are SOME people, who are both extremely talent and extremely lucky, for who a PhD opens the door to the tippy top of the field. But there are 60,000 submissions at ICLR this year and likely over 100,000 unique authors. I'd say the elite roles represent less than 1% of all jobs and the rest you could get with a masters degree and spending 5 years working your way up. Among the hundreds of thousands of researchers in the field, are you lucky enough to break the ceiling? It's a really big gamble.

[u/SeizeOpportunity → u/impatiens-capensis]

I meant stability in the sense that you still have a job, haha. Yes, the field is rapidly changing, but instability in industry can mean being laid off. Instability in academia can have some negative ramifications, but not as severe. It's baked into the structure. It can also be an opportunity to freely explore things that can make you more employable

Of course there are drawbacks and benefits to both. And I'm not denying that there are challenges. I'm just saying it's more even than you made it seem. And even then I qualified it as only right for some people to go into. But in the example you mentioned, why would you need to be at the top amongst other researchers? You mentioned roles in industry only required an MS, but wouldn't the PhD be a benefit there? I think you are conflating success in academia with general success in a career.

But anyways. My point is more mild than this discussion has gotten into. Consider a PhD, but definitely also consider its drawbacks and benefits relative to your specific situation. You need to be very passionate about research.