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[D] Machine Learning PhD failure? Navigating the harsh reality of graduating without publications (alien.top)

submitted 1 year ago by Training_Bet_7905@alien.top to c/machinelearning@academy.garden

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Hi ML community,

I'm nearing the end of my three-year PhD journey. Throughout this period, I've dedicated myself to producing a research paper annually, targeting top-tier conferences like ICML, ICLR, and NeurIPS. Despite my efforts and resubmissions, none of my papers made it through. As a result, my publication record consists solely of three manuscripts on arXiv.

My initial post-PhD ambition was to delve deeper into machine learning research at leading tech companies such as Facebook, Google, or Microsoft. However, my applications were turned down, primarily due to the lack of publications in prestigious conferences, which seems to be a crucial criterion for these roles.

Confronted with this setback and the pressing need to manage my finances, I shifted my focus to more traditional industry roles in consulting and finance. I've recently secured a position in quant finance, which, while exciting, means I won't have the bandwidth to revisit and resubmit my research papers.

Reflecting on this journey, I sometimes feel disheartened, questioning the value of my PhD experience, especially when I consider my lack of published work in major machine learning conferences.

I see other PhD students in my field publish 2 papers per year in these top conferences which makes me wonder whether I am a failure? I'm open to any thoughts or advice on my situation.

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[–] BigBayesian@alien.top 1 points 1 year ago

I think there's a lot of bias in how you're looking at the data. In particular, for someone trained to deal with noise, you're attributing your observations to signal, not noise. What's the acceptance rate at these conferences these days? It's so low it beggars belief. The review process exists during the same duration as ever (the briefest in academia), but the raw number of submissions has exploded. There's no serious way to stack rank that much data without multiple evaluations, and that's too hard / expensive. So the end ranking is largely noise, probably only weakly correlated with the "true" ranking that would be determined by a million ML profs doing nothing but reviewing papers all the time.

You have failed in the narrow sense that you didn't earn the laurels you needed to achieve your career goals. But that isn't to say that someone else, with your fortune but their ability, would have done differently. You gambled and didn't win the grand prize.

Please don't buy into the myth that those of us who've gotten luckier are so well-served by propagating - that this field is a serious meritocracy. There's just way too little signal and way too much noise to take that belief seriously.

At least you got something. You'll get about the same money, but fewer tshirts and snacks. And you'll have to dress better.