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What do you wish you had known before starting your PhD? (83)

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Growing 60 pts 0 followers
Father Muller Medical College · Posted
Clinical Medicine Economics Robotics & Automation

I want to start an honest conversation about something I have been thinking about for a while.

As a fourth-year PhD student, I have watched the academic publication ecosystem up close. The pressure to publish in high-impact journals has created perverse incentives:

  • Researchers cherry-pick results to show positive findings
  • Null results are systematically rejected
  • The same idea gets cut into multiple 'minimum publishable units' to inflate output
  • Citation rings inflate impact scores

What do you think? Is this a structural problem that needs policy-level intervention, or are there practical things individual researchers can do?

I am particularly interested in hearing from senior faculty who have seen this evolve over their careers.

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19 Replies

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Wajid Khan Growing 110 pts · Accepted answer

The short answer: it depends heavily on the journal and field, but here is a general framework.

If your null result is well-powered and the hypothesis was reasonable: Absolutely publish it. Null results in well-designed studies are as valuable as positive results. Journals like PLOS ONE explicitly welcome them.

If your study is underpowered: Be transparent about it. Report effect sizes and confidence intervals, not just p-values. A small, underpowered study with honest reporting is still a contribution.

What kills papers is when limitations are obvious but the authors have not addressed them.

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Vikram Bhatia Active 420 pts · Accepted answer

For Zotero vs BibTeX management, I moved to Zotero + Better BibTeX 3 years ago and have not looked back.

My workflow:

  1. Zotero browser connector captures papers instantly from ArXiv, Google Scholar, ACM DL, IEEE Xplore
  2. Better BibTeX generates a clean .bib file that auto-updates whenever I add a paper
  3. Overleaf directly pulls from the .bib file via Dropbox sync

One tip: create a Zotero collection per paper/project. When you export the .bib, export only that collection to keep it clean.

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Replying to Vikram Bhatia
Fatima Sheikh Growing 95 pts · Accepted answer

Much appreciated. I will restructure my proposal along these lines. The point about societal impact being substantive is something I would have gotten wrong.

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Replying to Vikram Bhatia
Suresh Iyer · Accepted answer

This is a known issue with XLM-R on code-mixed data. The MuRIL preprint has a section specifically comparing these.

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Replying to Vikram Bhatia
Bhavana Reddy Starting 30 pts · Accepted answer

This is very reassuring. I was worried the null result would kill the paper but your framing around transparency and effect sizes makes a lot of sense.

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Royal Dsouza Starting 30 pts · Accepted answer

Strongly agree with the point about choosing venues carefully. One paper in NeurIPS > five papers in obscure workshops.

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Neha Agarwal Growing 90 pts · Accepted answer

Strongly agree with the point about choosing venues carefully. One paper in NeurIPS > five papers in obscure workshops.

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Replying to Neha Agarwal
Zara Hussain Growing 55 pts · Accepted answer

Seconding the recommendation for Zotero. Game changer for managing references across multiple projects.

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Ashwin Murthy Distinguished 560 pts · Accepted answer

Open access is the right direction but the APCs are prohibitively expensive for many Indian researchers without institutional funding.

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Xena D'Souza Starting 25 pts · Accepted answer

For Zotero vs BibTeX management, I moved to Zotero + Better BibTeX 3 years ago and have not looked back.

My workflow:

  1. Zotero browser connector captures papers instantly from ArXiv, Google Scholar, ACM DL, IEEE Xplore
  2. Better BibTeX generates a clean .bib file that auto-updates whenever I add a paper
  3. Overleaf directly pulls from the .bib file via Dropbox sync

One tip: create a Zotero collection per paper/project. When you export the .bib, export only that collection to keep it clean.

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Zara Hussain Growing 55 pts · Accepted answer

Flower (flwr) is the most actively maintained and research-friendly federated learning framework right now. My group has been using it for 18 months on a healthcare project with 4 hospital sites.

Strengths:

  • Clean simulation API that lets you test on a single machine before deploying
  • Good support for custom aggregation strategies (FedProx, FedNova)
  • Active Discord community with quick responses from the maintainers

For non-IID data specifically, look at the FedProx strategy.it handles heterogeneous data distributions much better than FedAvg.

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Nandita Ghosh Distinguished 720 pts · Accepted answer

Could you clarify what you mean by results-blind review? I have heard of it but never understood how it works in practice. Wouldn't reviewers need to see results to evaluate whether the methodology is sound?

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Replying to Nandita Ghosh
Harini Balakrishnan Active 215 pts · Accepted answer

Highly recommend checking out the PMRF portal for the actual numbers.they update the stipend structure annually.

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Replying to Nandita Ghosh
Chetan Jain Growing 100 pts · Accepted answer

Strongly agree with the point about choosing venues carefully. One paper in NeurIPS > five papers in obscure workshops.

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Geeta Rao · Accepted answer

For longitudinal data with missing values, mixed-effects models handle this more gracefully than imputation in most cases.

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Rekha Shetty Starting 40 pts · Accepted answer

Check whether your institution has a Springer/Elsevier waiver agreement.many NITs and IITs do.

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Replying to Rekha Shetty
Jaya Lakshmanan Growing 50 pts · Accepted answer

Seconding the recommendation for Zotero. Game changer for managing references across multiple projects.

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Replying to Rekha Shetty
Kiran Yadav Growing 130 pts · Accepted answer

Thank you for this detailed answer! A quick follow-up: when you mention cosine learning rate with warm-up, are you warming up the LoRA parameters specifically or the entire model including the frozen backbone?

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Replying to Rekha Shetty
Lakshmi Devi Growing 75 pts · Accepted answer

Marking this as the accepted answer. Incredibly helpful and specific. Really appreciate you taking the time.