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Reflections on completing my PhD at IIT Madras.the good, the hard, the lessons

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Active 480 pts 0 followers
University of Mysore · Posted
Science Communication

The honest answer to 'is a PhD worth it in India in 2025'

I will answer this question honestly because I see a lot of either uncritical enthusiasm or doom-and-gloom on this forum.

A PhD is worth it if:

  • You have a specific intellectual problem you are genuinely obsessed with
  • You want a career in research, academia, or high-end R&D at companies that value PhD credentials
  • You are comfortable with a 4–6 year period of relatively low pay and high uncertainty in exchange for intellectual freedom
  • You have a supervisor who is genuinely good at mentoring (this is the single biggest variable)

A PhD is probably not worth it if:

  • You want it for the credential rather than the research itself
  • You are going into fields (software engineering, finance, many business areas) where a PhD does not provide a salary premium
  • You are relying on it to 'figure out' what you want to do.that is what a master's degree is for

The Indian academic job market is brutal. If you want to be a professor at an IIT or IISC, you will likely need postdoctoral experience and a publication record that takes 8–10 years post-bachelor's to build.

But if research is genuinely what you want to do.it is absolutely worth it.

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45 Replies

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Chirag Mehta Starting 15 pts · Accepted answer

The ethics review situation in Indian universities is actually more complex than most people realize.

There is no uniform national framework equivalent to the US Common Rule. Each institution has its own Institutional Ethics Committee (IEC) or Institutional Review Board (IRB).

For anonymous survey research with no identifiable data and no vulnerable populations: most Indian IECs would classify this as exempt, but 'exempt' still needs a formal determination from the IEC.it is not self-certifying.

My practical advice: go to your institution's research ethics office now, describe what you did, and request an exempt determination in writing. Better to have documentation than to discover the issue during thesis review.

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Om Prakash Growing 55 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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Anita Rao · Accepted answer

This is really helpful context. One more question: for the ethics committee approval, does the institution where the data is collected or the institution where the analysis is performed need to be the primary ethics approver?

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Varsha Pillai Growing 60 pts · Accepted answer

Great question.I went through something very similar in my second year.

The key insight for me was that LoRA is actually quite well-suited for NER tasks, especially in low-resource settings. I would recommend:

  1. Use LoRA with r=8 or r=16.don't go higher for 8K samples
  2. Apply LoRA to attention layers only, not the feed-forward layers
  3. Use a cosine learning rate schedule with warm-up (10% of steps)

For Telugu-English code-mixed NER specifically, you might also look at MuRIL.it is pretrained on Indian language data and often outperforms XLM-R on Indic tasks even with less fine-tuning data.

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Ashwin Murthy Distinguished 560 pts · Accepted answer

This question comes up a lot. The answer really depends on your specific field and what your committee values.

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Replying to Ashwin Murthy
Rohan Desai Distinguished 950 pts · Accepted answer

This is really helpful context. One more question: for the ethics committee approval, does the institution where the data is collected or the institution where the analysis is performed need to be the primary ethics approver?

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Replying to Ashwin Murthy
Lalitha Mohan Active 230 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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Admin NITK · Accepted answer

This question comes up a lot. The answer really depends on your specific field and what your committee values.

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Vikram Bhatia Active 420 pts · Accepted answer

Just to make sure I understand the Zotero workflow correctly.is the .bib file synced to Overleaf automatically every time you add a new paper, or do you need to trigger an export manually?

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Asha Pillai Distinguished 880 pts · Accepted answer

FDR (Benjamini-Hochberg) is widely accepted and preferable to Bonferroni when you have many tests and limited power. The key is to be explicit about which correction you used and why.

On replication: No independent cohort is a genuine limitation but not a dealbreaker for rare disease research, where cohort availability is a known constraint. Many high-quality papers acknowledge this and still get published in good journals. Frame it as future work.

Power analysis: Yes, report it. Showing you are aware of the limitation is better than not mentioning it.

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Replying to Asha Pillai
Varsha Pillai Growing 60 pts · Accepted answer

+1 to everything said above. My experience was identical.

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Replying to Asha Pillai
Manish Tiwari Starting 10 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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Shiva Prasad Active 480 pts · Accepted answer

This question comes up a lot. The answer really depends on your specific field and what your committee values.

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Preethi Anand Distinguished 690 pts · Accepted answer

I think you are conflating two separate problems here. The publish-or-perish culture creates pressure, yes.but the solution is not to criticize researchers who are navigating an unfair system. The real problem is with evaluation committees who treat publication count as a proxy for research quality. Fix the evaluation, and the incentives change.

Also worth noting: open review has been implemented in some fields and has its own problems. It can disadvantage early-career researchers who fear retaliation from senior colleagues they have reviewed critically.

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Replying to Preethi Anand
Karthik Rajan Growing 180 pts · Accepted answer

This is really helpful context. One more question: for the ethics committee approval, does the institution where the data is collected or the institution where the analysis is performed need to be the primary ethics approver?

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Prakash Iyer Distinguished 640 pts · 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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Prakash Iyer Distinguished 640 pts · Accepted answer

I think you are conflating two separate problems here. The publish-or-perish culture creates pressure, yes.but the solution is not to criticize researchers who are navigating an unfair system. The real problem is with evaluation committees who treat publication count as a proxy for research quality. Fix the evaluation, and the incentives change.

Also worth noting: open review has been implemented in some fields and has its own problems. It can disadvantage early-career researchers who fear retaliation from senior colleagues they have reviewed critically.

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Replying to Prakash Iyer
Om Prakash Growing 55 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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Kiran Yadav Growing 130 pts · Accepted answer

When you say 'multiple runs with confidence intervals', do you mean running the full training pipeline multiple times with different random seeds and reporting mean ± std? Or something more statistically rigorous?

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Xena D'Souza Starting 25 pts · Accepted answer

I have a slightly different take from my experience in industry research. The reproducibility crisis is real but unevenly distributed. Fields with strong engineering culture (computational biology, ML with benchmarks) have actually improved significantly in the last 5 years. The bigger problem is in fields where data sharing is structurally difficult.clinical medicine, behavioral economics.

The ML community's move toward open code and reproducibility checklists has been genuinely effective.

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Sunil Bhattacharya Active 390 pts · Accepted answer

I think you are conflating two separate problems here. The publish-or-perish culture creates pressure, yes.but the solution is not to criticize researchers who are navigating an unfair system. The real problem is with evaluation committees who treat publication count as a proxy for research quality. Fix the evaluation, and the incentives change.

Also worth noting: open review has been implemented in some fields and has its own problems. It can disadvantage early-career researchers who fear retaliation from senior colleagues they have reviewed critically.

0
Varsha Pillai Growing 60 pts · Accepted answer

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

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Suresh Iyer · Accepted answer

The ethics review situation in Indian universities is actually more complex than most people realize.

There is no uniform national framework equivalent to the US Common Rule. Each institution has its own Institutional Ethics Committee (IEC) or Institutional Review Board (IRB).

For anonymous survey research with no identifiable data and no vulnerable populations: most Indian IECs would classify this as exempt, but 'exempt' still needs a formal determination from the IEC.it is not self-certifying.

My practical advice: go to your institution's research ethics office now, describe what you did, and request an exempt determination in writing. Better to have documentation than to discover the issue during thesis review.

0
Replying to Suresh Iyer
Harini Balakrishnan Active 215 pts · Accepted answer

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

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Replying to Suresh Iyer
Arjun Venkatesan Growing 195 pts · 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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Tara Singh Starting 5 pts · Accepted answer

I think you are conflating two separate problems here. The publish-or-perish culture creates pressure, yes.but the solution is not to criticize researchers who are navigating an unfair system. The real problem is with evaluation committees who treat publication count as a proxy for research quality. Fix the evaluation, and the incentives change.

Also worth noting: open review has been implemented in some fields and has its own problems. It can disadvantage early-career researchers who fear retaliation from senior colleagues they have reviewed critically.

0
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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Ashwin Murthy Distinguished 560 pts · Accepted answer

The IEEE TPAMI turnaround in my case was 7 months for the first review. Plan accordingly.

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Replying to Ashwin Murthy
Gopal Naidu · Accepted answer

This is really helpful context. One more question: for the ethics committee approval, does the institution where the data is collected or the institution where the analysis is performed need to be the primary ethics approver?

0
Replying to Ashwin Murthy
Royal Dsouza Starting 30 pts · Accepted answer

This question comes up a lot. The answer really depends on your specific field and what your committee values.

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Replying to Ashwin Murthy
Quamar Ahmed Growing 65 pts · Accepted answer

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

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Anita Rao · 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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Ravi Patel Starting 25 pts · Accepted answer

This is really helpful context. One more question: for the ethics committee approval, does the institution where the data is collected or the institution where the analysis is performed need to be the primary ethics approver?

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Dinesh Kulkarni Distinguished 730 pts · Accepted answer

This question comes up a lot. The answer really depends on your specific field and what your committee values.

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Sowmya Narayanan Active 310 pts · Accepted answer

+1 to everything said above. My experience was identical.

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Preethi Anand Distinguished 690 pts · Accepted answer

Just to make sure I understand the Zotero workflow correctly.is the .bib file synced to Overleaf automatically every time you add a new paper, or do you need to trigger an export manually?

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Replying to Preethi Anand
Suresh Iyer · Accepted answer

Thank you! The reference to MuRIL is particularly useful.I had not considered it as an alternative to XLM-R for Indic languages.

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Replying to Preethi Anand
Priya Nair · Accepted answer

+1 to everything said above. My experience was identical.

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Lalitha Mohan Active 230 pts · Accepted answer

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

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Om Prakash Growing 55 pts · Accepted answer

I can answer your question about IEEE Transactions review timelines from my experience submitting to IEEE TNNLS.

For Q1 IEEE journals, expect:

  • Initial desk review: 2–4 weeks
  • Full peer review: 3–6 months
  • Major revision decision: another 2–3 months for re-review

As for code and data, most IEEE journals now request code upon acceptance, not submission. Regarding your 2.3% improvement.that is borderline. You will need very strong experimental rigor: multiple runs, confidence intervals, and significance tests.

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Prakash Iyer Distinguished 640 pts · Accepted answer

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

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Replying to Prakash Iyer
Rajesh Kumar · Accepted answer

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

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Admin NITK · 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 Admin NITK
Anita Rao · Accepted answer

If you are not already using a reading group format with your students, I would strongly recommend it. Forces everyone to articulate what they read.

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Bindiya Thomas Growing 65 pts · Accepted answer

I can answer your question about IEEE Transactions review timelines from my experience submitting to IEEE TNNLS.

For Q1 IEEE journals, expect:

  • Initial desk review: 2–4 weeks
  • Full peer review: 3–6 months
  • Major revision decision: another 2–3 months for re-review

As for code and data, most IEEE journals now request code upon acceptance, not submission. Regarding your 2.3% improvement.that is borderline. You will need very strong experimental rigor: multiple runs, confidence intervals, and significance tests.